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2020 – today
- 2024
[j17]Depeng Li, Tianqi Wang, Junwei Chen, Kenji Kawaguchi, Cheng Lian
, Zhigang Zeng:
Multi-view class incremental learning. Inf. Fusion 102: 102021 (2024)- [j16]Zheyuan Hu, Khemraj Shukla, George Em Karniadakis, Kenji Kawaguchi:
Tackling the curse of dimensionality with physics-informed neural networks. Neural Networks 176: 106369 (2024) - [c66]Depeng Li, Tianqi Wang, Junwei Chen, Qining Ren, Kenji Kawaguchi, Zhigang Zeng:
Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding. AAAI 2024: 13464-13473 - [c65]Zhiyuan Liu, Yaorui Shi, An Zhang, Sihang Li, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua:
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining. ACL (Findings) 2024: 5353-5377 - [c64]Zhiyuan Liu, An Zhang, Hao Fei, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua:
ProtT3: Protein-to-Text Generation for Text-based Protein Understanding. ACL (1) 2024: 5949-5966 - [c63]Do Xuan Long, Yiran Zhao, Hannah Brown, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Shieh, Junxian He:
Prompt Optimization via Adversarial In-Context Learning. ACL (1) 2024: 7308-7327 - [c62]Xiang Li, Qianli Shen, Kenji Kawaguchi:
VA3: Virtually Assured Amplification Attack on Probabilistic Copyright Protection for Text-to-Image Generative Models. CVPR 2024: 12363-12373 - [c61]Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
Simple Hierarchical Planning with Diffusion. ICLR 2024 - [c60]Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Self-Supervised Dataset Distillation for Transfer Learning. ICLR 2024 - [c59]Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian:
Towards 3D Molecule-Text Interpretation in Language Models. ICLR 2024 - [c58]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao:
Scalable and Effective Implicit Graph Neural Networks on Large Graphs. ICLR 2024 - [c57]Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu:
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness. ICLR 2024 - [c56]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML 2024 - [c55]Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. ICML 2024 - [c54]Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi:
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. ICML 2024 - [c53]Seul Lee, Seanie Lee, Kenji Kawaguchi, Sung Ju Hwang:
Drug Discovery with Dynamic Goal-aware Fragments. ICML 2024 - [c52]Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao:
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. ICML 2024 - [c51]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. ICML 2024 - [c50]Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi:
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline. ICML 2024 - [c49]Shihao Zhang, Kenji Kawaguchi, Angela Yao:
Deep Regression Representation Learning with Topology. ICML 2024 - [i107]Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi:
Can AI Be as Creative as Humans? CoRR abs/2401.01623 (2024) - [i106]Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
Simple Hierarchical Planning with Diffusion. CoRR abs/2401.02644 (2024) - [i105]Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi:
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright Breaches Without Adjusting Finetuning Pipeline. CoRR abs/2401.04136 (2024) - [i104]Depeng Li, Tianqi Wang, Junwei Chen, Qining Ren, Kenji Kawaguchi, Zhigang Zeng:
Towards Continual Learning Desiderata via HSIC-Bottleneck Orthogonalization and Equiangular Embedding. CoRR abs/2401.09067 (2024) - [i103]Sihang Li, Zhiyuan Liu, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian:
Towards 3D Molecule-Text Interpretation in Language Models. CoRR abs/2401.13923 (2024) - [i102]Zheyuan Hu, Zhongqiang Zhang, George Em Karniadakis, Kenji Kawaguchi:
Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck Equations. CoRR abs/2402.07465 (2024) - [i101]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR abs/2402.13368 (2024) - [i100]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR abs/2402.15170 (2024) - [i99]Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao:
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. CoRR abs/2402.16305 (2024) - [i98]Yiran Zhao, Wenxuan Zhang, Guizhen Chen, Kenji Kawaguchi, Lidong Bing:
How do Large Language Models Handle Multilingualism? CoRR abs/2402.18815 (2024) - [i97]Yiran Zhao, Wenxuan Zhang, Huiming Wang, Kenji Kawaguchi, Lidong Bing:
AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging. CoRR abs/2402.18913 (2024) - [i96]Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh:
Accelerating Greedy Coordinate Gradient via Probe Sampling. CoRR abs/2403.01251 (2024) - [i95]Yang Zhang, Teoh Tze Tzun, Lim Wei Hern, Tiviatis Sim, Kenji Kawaguchi:
Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models. CoRR abs/2403.06381 (2024) - [i94]Yingtian Zou, Kenji Kawaguchi, Yingnan Liu, Jiashuo Liu, Mong-Li Lee, Wynne Hsu:
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness. CoRR abs/2403.06392 (2024) - [i93]Taorui Wang, Zheyuan Hu, Kenji Kawaguchi, Zhongqiang Zhang, George Em Karniadakis:
Tensor neural networks for high-dimensional Fokker-Planck equations. CoRR abs/2404.05615 (2024) - [i92]Shihao Zhang, Kenji Kawaguchi, Angela Yao:
Deep Regression Representation Learning with Topology. CoRR abs/2404.13904 (2024) - [i91]Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P. Lillicrap, Kenji Kawaguchi, Michael Shieh:
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning. CoRR abs/2405.00451 (2024) - [i90]Zhiyuan Liu, An Zhang, Hao Fei, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua:
ProtT3: Protein-to-Text Generation for Text-based Protein Understanding. CoRR abs/2405.12564 (2024) - [i89]Zhiyuan Liu, Yaorui Shi, An Zhang, Sihang Li, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua:
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining. CoRR abs/2405.14225 (2024) - [i88]Yang Zhang, Yawei Li, Xinpeng Wang, Qianli Shen, Barbara Plank, Bernd Bischl, Mina Rezaei, Kenji Kawaguchi:
FinerCut: Finer-grained Interpretable Layer Pruning for Large Language Models. CoRR abs/2405.18218 (2024) - [i87]Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain:
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR abs/2405.18540 (2024) - [i86]Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi:
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. CoRR abs/2406.02847 (2024) - [i85]Chang Chen, Junyeob Baek, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin Ahn:
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer. CoRR abs/2406.06793 (2024) - [i84]Zheyuan Hu, Zhongqiang Zhang, George Em Karniadakis, Kenji Kawaguchi:
Score-fPINN: Fractional Score-Based Physics-Informed Neural Networks for High-Dimensional Fokker-Planck-Levy Equations. CoRR abs/2406.11676 (2024) - [i83]Zheyuan Hu, Kenji Kawaguchi, Zhongqiang Zhang, George Em Karniadakis:
Tackling the Curse of Dimensionality in Fractional and Tempered Fractional PDEs with Physics-Informed Neural Networks. CoRR abs/2406.11708 (2024) - [i82]Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi:
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization. CoRR abs/2406.14095 (2024) - [i81]Leon Lin, Hannah Brown, Kenji Kawaguchi, Michael Shieh:
Single Character Perturbations Break LLM Alignment. CoRR abs/2407.03232 (2024) - [i80]Hannah Brown, Leon Lin, Kenji Kawaguchi, Michael Shieh:
Self-Evaluation as a Defense Against Adversarial Attacks on LLMs. CoRR abs/2407.03234 (2024) - [i79]Xuan Long Do, Hai Nguyen Ngoc, Tiviatis Sim, Hieu Dao, Shafiq Joty, Kenji Kawaguchi, Nancy F. Chen, Min-Yen Kan:
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs. CoRR abs/2408.08656 (2024) - [i78]Zheyuan Hu, Nazanin Ahmadi Daryakenari, Qianli Shen, Kenji Kawaguchi, George Em Karniadakis:
State-space models are accurate and efficient neural operators for dynamical systems. CoRR abs/2409.03231 (2024) - [i77]Yang Zhang, Yanfei Dong, Kenji Kawaguchi:
Investigating Layer Importance in Large Language Models. CoRR abs/2409.14381 (2024) - 2023
- [j15]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology. Eng. Appl. Artif. Intell. 126: 107183 (2023) - [j14]Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le:
Combined scaling for zero-shot transfer learning. Neurocomputing 555: 126658 (2023) - [j13]Haonan Wang, Jieyu Zhang, Qi Zhu, Wei Huang, Kenji Kawaguchi, Xiaokui Xiao:
Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph. Trans. Mach. Learn. Res. 2023 (2023) - [c48]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI 2023: 8825-8833 - [c47]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI 2023: 1248-1255 - [c46]James Xu Zhao, Yuxi Xie, Kenji Kawaguchi, Junxian He, Michael Qizhe Xie:
Automatic Model Selection with Large Language Models for Reasoning. EMNLP (Findings) 2023: 758-783 - [c45]Zhiyuan Liu, Sihang Li, Yanchen Luo, Hao Fei, Yixin Cao, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua:
MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. EMNLP 2023: 15623-15638 - [c44]Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Ankit Vani, Michael Noukhovitch, Kenji Kawaguchi, Aaron C. Courville:
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. ICLR 2023 - [c43]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi:
Self-Distillation for Further Pre-training of Transformers. ICLR 2023 - [c42]Dong Bok Lee, Seanie Lee, Kenji Kawaguchi, Yunji Kim, Jihwan Bang, Jung-Woo Ha, Sung Ju Hwang:
Self-Supervised Set Representation Learning for Unsupervised Meta-Learning. ICLR 2023 - [c41]Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A. H. Castro Neto, Kostya S. Novoselov, Shuicheng Yan:
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. ICLR 2023 - [c40]Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang:
How Does Information Bottleneck Help Deep Learning? ICML 2023: 16049-16096 - [c39]Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. ICML 2023: 21715-21729 - [c38]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. ICML 2023: 30689-30705 - [c37]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. ICML 2023: 34431-34455 - [c36]Jeffrey Willette, Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation. ICML 2023: 37008-37041 - [c35]Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. KDD 2023: 93-104 - [c34]Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang:
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. NeurIPS 2023 - [c33]Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua:
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. NeurIPS 2023 - [c32]Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi:
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. NeurIPS 2023 - [c31]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. NeurIPS 2023 - [c30]Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, Michael Qizhe Xie:
Self-Evaluation Guided Beam Search for Reasoning. NeurIPS 2023 - [c29]Yingtian Zou, Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi:
MixupE: Understanding and improving Mixup from directional derivative perspective. UAI 2023: 2597-2607 - [i76]Aviv Shamsian, Aviv Navon, Neta Glazer, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Auxiliary Learning as an Asymmetric Bargaining Game. CoRR abs/2301.13501 (2023) - [i75]Tianbo Li, Min Lin, Zheyuan Hu, Kunhao Zheng, Giovanni Vignale, Kenji Kawaguchi, A. H. Castro Neto, Kostya S. Novoselov, Shuicheng Yan:
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. CoRR abs/2303.00399 (2023) - [i74]Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun:
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. CoRR abs/2303.00633 (2023) - [i73]Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou:
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR abs/2304.03935 (2023) - [i72]Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, Xu Zhao, Min-Yen Kan, Junxian He, Qizhe Xie:
Decomposition Enhances Reasoning via Self-Evaluation Guided Decoding. CoRR abs/2305.00633 (2023) - [i71]Xu Zhao, Yuxi Xie, Kenji Kawaguchi, Junxian He, Qizhe Xie:
Automatic Model Selection with Large Language Models for Reasoning. CoRR abs/2305.14333 (2023) - [i70]Minki Kang, Seanie Lee, Jinheon Baek, Kenji Kawaguchi, Sung Ju Hwang:
Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. CoRR abs/2305.18395 (2023) - [i69]Kenji Kawaguchi, Zhun Deng, Xu Ji, Jiaoyang Huang:
How Does Information Bottleneck Help Deep Learning? CoRR abs/2305.18887 (2023) - [i68]Zike Wu, Pan Zhou, Kenji Kawaguchi, Hanwang Zhang:
Fast Diffusion Model. CoRR abs/2306.06991 (2023) - [i67]Depeng Li, Tianqi Wang, Junwei Chen, Kenji Kawaguchi, Cheng Lian, Zhigang Zeng:
Multi-View Class Incremental Learning. CoRR abs/2306.09675 (2023) - [i66]Depeng Li, Tianqi Wang, Bingrong Xu, Kenji Kawaguchi, Zhigang Zeng, Ponnuthurai Nagaratnam Suganthan:
IF2Net: Innately Forgetting-Free Networks for Continual Learning. CoRR abs/2306.10480 (2023) - [i65]Zheyuan Hu, Khemraj Shukla, George Em Karniadakis, Kenji Kawaguchi:
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks. CoRR abs/2307.12306 (2023) - [i64]Yawei Li, Yang Zhang, Kenji Kawaguchi, Ashkan Khakzar, Bernd Bischl, Mina Rezaei:
A Dual-Perspective Approach to Evaluating Feature Attribution Methods. CoRR abs/2308.08949 (2023) - [i63]Dong Bok Lee, Seanie Lee, Joonho Ko, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Self-Supervised Dataset Distillation for Transfer Learning. CoRR abs/2310.06511 (2023) - [i62]Yang Zhang, Yawei Li, Hannah Brown, Mina Rezaei, Bernd Bischl, Philip H. S. Torr, Ashkan Khakzar, Kenji Kawaguchi:
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments. CoRR abs/2310.06514 (2023) - [i61]Qianli Shen, Wai Hoh Tang, Zhun Deng, Apostolos F. Psaros, Kenji Kawaguchi:
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification. CoRR abs/2310.06923 (2023) - [i60]Zhiyuan Liu, Sihang Li, Yanchen Luo, Hao Fei, Yixin Cao, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua:
MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. CoRR abs/2310.12798 (2023) - [i59]Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, Tat-Seng Chua:
Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. CoRR abs/2310.14753 (2023) - [i58]Xuan Long Do, Kenji Kawaguchi, Min-Yen Kan, Nancy F. Chen:
ChOiRe: Characterizing and Predicting Human Opinions with Chain of Opinion Reasoning. CoRR abs/2311.08385 (2023) - [i57]Yang Zhang, Teoh Tze Tzun, Lim Wei Hern, Haonan Wang, Kenji Kawaguchi:
Investigating Copyright Issues of Diffusion Models under Practical Scenarios. CoRR abs/2311.12803 (2023) - [i56]Zheyuan Hu, Zhouhao Yang, Yezhen Wang, George Em Karniadakis, Kenji Kawaguchi:
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs. CoRR abs/2311.15283 (2023) - [i55]Xiang Li, Qianli Shen, Kenji Kawaguchi:
Probabilistic Copyright Protection Can Fail for Text-to-Image Generative Models. CoRR abs/2312.00057 (2023) - [i54]Kerui Gu, Zhihao Li, Shiyong Liu, Jianzhuang Liu, Songcen Xu, Youliang Yan, Michael Bi Mi, Kenji Kawaguchi, Angela Yao:
Learning Unorthogonalized Matrices for Rotation Estimation. CoRR abs/2312.00462 (2023) - [i53]Xuan Long Do, Yiran Zhao, Hannah Brown, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Qizhe Xie, Junxian He:
Prompt Optimization via Adversarial In-Context Learning. CoRR abs/2312.02614 (2023) - [i52]Zheyuan Hu, Zekun Shi, George Em Karniadakis, Kenji Kawaguchi:
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks. CoRR abs/2312.14499 (2023) - 2022
- [j12]Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis:
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. Neurocomputing 468: 165-180 (2022) - [j11]Apostolos F. Psaros, Kenji Kawaguchi, George Em Karniadakis:
Meta-learning PINN loss functions. J. Comput. Phys. 458: 111121 (2022) - [j10]Kenji Kawaguchi, Linjun Zhang, Zhun Deng:
Understanding Dynamics of Nonlinear Representation Learning and Its Application. Neural Comput. 34(4): 991-1018 (2022) - [j9]Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, Arno Solin, Yoshua Bengio, David Lopez-Paz:
Interpolation consistency training for semi-supervised learning. Neural Networks 145: 90-106 (2022) - [j8]Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio:
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks 154: 218-233 (2022) - [j7]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? SIAM J. Sci. Comput. 44(5): 3158- (2022) - [c28]Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang:
Robustness Implies Generalization via Data-Dependent Generalization Bounds. ICML 2022: 10866-10894 - [c27]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. ICML 2022: 16428-16446 - [c26]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. ICML 2022: 26135-26160 - [c25]Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes:
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS 2022 - [c24]Seanie Lee, Bruno Andreis, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Set-based Meta-Interpolation for Few-Task Meta-Learning. NeurIPS 2022 - [c23]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao:
MGNNI: Multiscale Graph Neural Networks with Implicit Layers. NeurIPS 2022 - [c22]Siddharth Bhatia, Arjit Jain, Shivin Srivastava, Kenji Kawaguchi, Bryan Hooi:
MemStream: Memory-Based Streaming Anomaly Detection. WWW 2022: 610-621 - [i51]Zhiyuan Liu, Yixin Cao, Fuli Feng, Xiang Wang, Xindi Shang, Jie Tang, Kenji Kawaguchi, Tat-Seng Chua:
Training Free Graph Neural Networks for Graph Matching. CoRR abs/2201.05349 (2022) - [i50]Shivin Srivastava, Kenji Kawaguchi, Vaibhav Rajan:
ExpertNet: A Symbiosis of Classification and Clustering. CoRR abs/2201.06344 (2022) - [i49]Aviv Navon, Aviv Shamsian, Idan Achituve, Haggai Maron, Kenji Kawaguchi, Gal Chechik, Ethan Fetaya:
Multi-Task Learning as a Bargaining Game. CoRR abs/2202.01017 (2022) - [i48]Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi:
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR abs/2202.01334 (2022) - [i47]Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao:
EIGNN: Efficient Infinite-Depth Graph Neural Networks. CoRR abs/2202.10720 (2022) - [i46]Samuel Lavoie, Christos Tsirigotis, Max Schwarzer, Kenji Kawaguchi, Ankit Vani, Aaron C. Courville:
Simplicial Embeddings in Self-Supervised Learning and Downstream Classification. CoRR abs/2204.00616 (2022) - [i45]Seanie Lee, Andreis Bruno, Kenji Kawaguchi, Juho Lee, Sung Ju Hwang:
Set-based Meta-Interpolation for Few-Task Meta-Learning. CoRR abs/2205.09990 (2022) - [i44]Kenji Kawaguchi, Zhun Deng, Kyle Luh, Jiaoyang Huang:
Robustness Implies Generalization via Data-Dependent Generalization Bounds. CoRR abs/2206.13497 (2022) - [i43]Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf:
Discrete Key-Value Bottleneck. CoRR abs/2207.11240 (2022) - [i42]Seanie Lee, Minki Kang, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi:
Self-Distillation for Further Pre-training of Transformers. CoRR abs/2210.02871 (2022) - [i41]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao:
MGNNI: Multiscale Graph Neural Networks with Implicit Layers. CoRR abs/2210.08353 (2022) - [i40]Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio:
GFlowOut: Dropout with Generative Flow Networks. CoRR abs/2210.12928 (2022) - [i39]Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes:
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR abs/2211.00247 (2022) - [i38]Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb:
Neural Active Learning on Heteroskedastic Distributions. CoRR abs/2211.00928 (2022) - [i37]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology. CoRR abs/2211.08939 (2022) - [i36]Vikas Verma, Sarthak Mittal, Wai Hoh Tang, Hieu Pham, Juho Kannala, Yoshua Bengio, Arno Solin, Kenji Kawaguchi:
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective. CoRR abs/2212.13381 (2022) - 2021
- [c21]Kenji Kawaguchi, Qingyun Sun:
A Recipe for Global Convergence Guarantee in Deep Neural Networks. AAAI 2021: 8074-8082 - [c20]Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang:
GraphMix: Improved Training of GNNs for Semi-Supervised Learning. AAAI 2021: 10024-10032 - [c19]Zhun Deng, Jiaoyang Huang, Kenji Kawaguchi:
How Shrinking Gradient Noise Helps the Performance of Neural Networks. IEEE BigData 2021: 1002-1007 - [c18]Kenji Kawaguchi:
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers. ICLR 2021 - [c17]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou:
How Does Mixup Help With Robustness and Generalization? ICLR 2021 - [c16]Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le:
Towards Domain-Agnostic Contrastive Learning. ICML 2021: 10530-10541 - [c15]Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi:
Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth. ICML 2021: 11592-11602 - [c14]Clement Gehring, Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization. NeurIPS 2021: 703-714 - [c13]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. NeurIPS 2021: 2109-2121 - [c12]Ferran Alet, Dylan Doblar, Allan Zhou, Josh Tenenbaum, Kenji Kawaguchi, Chelsea Finn:
Noether Networks: meta-learning useful conserved quantities. NeurIPS 2021: 16384-16397 - [c11]Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao:
EIGNN: Efficient Infinite-Depth Graph Neural Networks. NeurIPS 2021: 18762-18773 - [c10]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou:
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS 2021: 25179-25191 - [c9]Ferran Alet, Maria Bauzá, Kenji Kawaguchi, Nurullah Giray Kuru, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time. NeurIPS 2021: 29206-29217 - [i35]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou:
When and How Mixup Improves Calibration. CoRR abs/2102.06289 (2021) - [i34]Kenji Kawaguchi:
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers. CoRR abs/2102.07346 (2021) - [i33]Shivin Srivastava, Siddharth Bhatia, Lingxiao Huang, Lim Jun Heng, Kenji Kawaguchi, Vaibhav Rajan:
CAC: A Clustering Based Framework for Classification. CoRR abs/2102.11872 (2021) - [i32]Kenji Kawaguchi, Qingyun Sun:
A Recipe for Global Convergence Guarantee in Deep Neural Networks. CoRR abs/2104.05785 (2021) - [i31]Keyulu Xu, Mozhi Zhang, Stefanie Jegelka, Kenji Kawaguchi:
Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth. CoRR abs/2105.04550 (2021) - [i30]Ameya D. Jagtap, Yeonjong Shin, Kenji Kawaguchi, George Em Karniadakis:
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions. CoRR abs/2105.09513 (2021) - [i29]Siddharth Bhatia, Arjit Jain, Shivin Srivastava, Kenji Kawaguchi, Bryan Hooi:
MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift. CoRR abs/2106.03837 (2021) - [i28]Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou:
Adversarial Training Helps Transfer Learning via Better Representations. CoRR abs/2106.10189 (2021) - [i27]Kenji Kawaguchi, Linjun Zhang, Zhun Deng:
Understanding Dynamics of Nonlinear Representation Learning and Its Application. CoRR abs/2106.14836 (2021) - [i26]Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio:
Discrete-Valued Neural Communication. CoRR abs/2107.02367 (2021) - [i25]Apostolos F. Psaros, Kenji Kawaguchi, George Em Karniadakis:
Meta-learning PINN loss functions. CoRR abs/2107.05544 (2021) - [i24]Zheyuan Hu, Ameya D. Jagtap, George Em Karniadakis, Kenji Kawaguchi:
When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? CoRR abs/2109.09444 (2021) - [i23]Ferran Alet, Dylan Doblar, Allan Zhou, Joshua B. Tenenbaum, Kenji Kawaguchi, Chelsea Finn:
Noether Networks: Meta-Learning Useful Conserved Quantities. CoRR abs/2112.03321 (2021) - 2020
- [j6]Ameya D. Jagtap, Kenji Kawaguchi, George Em Karniadakis:
Adaptive activation functions accelerate convergence in deep and physics-informed neural networks. J. Comput. Phys. 404 (2020) - [c8]Kenji Kawaguchi, Haihao Lu:
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization. AISTATS 2020: 669-679 - [c7]Kenji Kawaguchi, Leslie Pack Kaelbling:
Elimination of All Bad Local Minima in Deep Learning. AISTATS 2020: 853-863 - [i22]Ferran Alet, Kenji Kawaguchi, Tomás Lozano-Pérez, Leslie Pack Kaelbling:
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time. CoRR abs/2009.10623 (2020) - [i21]Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou:
How Does Mixup Help With Robustness and Generalization? CoRR abs/2010.04819 (2020) - [i20]Vikas Verma, Minh-Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc V. Le:
Towards Domain-Agnostic Contrastive Learning. CoRR abs/2011.04419 (2020)
2010 – 2019
- 2019
- [j5]Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Effect of Depth and Width on Local Minima in Deep Learning. Neural Comput. 31(7): 1462-1498 (2019) - [j4]Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Every Local Minimum Value Is the Global Minimum Value of Induced Model in Nonconvex Machine Learning. Neural Comput. 31(12): 2293-2323 (2019) - [j3]Kenji Kawaguchi, Yoshua Bengio:
Depth with nonlinearity creates no bad local minima in ResNets. Neural Networks 118: 167-174 (2019) - [c6]Kenji Kawaguchi, Jiaoyang Huang:
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes. Allerton 2019: 92-99 - [i19]Kenji Kawaguchi, Leslie Pack Kaelbling:
Elimination of All Bad Local Minima in Deep Learning. CoRR abs/1901.00279 (2019) - [i18]Jascha Sohl-Dickstein, Kenji Kawaguchi:
Eliminating all bad Local Minima from Loss Landscapes without even adding an Extra Unit. CoRR abs/1901.03909 (2019) - [i17]Kenji Kawaguchi, Leslie Pack Kaelbling:
Every Local Minimum is a Global Minimum of an Induced Model. CoRR abs/1904.03673 (2019) - [i16]Kenji Kawaguchi, Haihao Lu:
A Stochastic First-Order Method for Ordered Empirical Risk Minimization. CoRR abs/1907.04371 (2019) - [i15]Kenji Kawaguchi, Jiaoyang Huang:
Gradient Descent Finds Global Minima for Generalizable Deep Neural Networks of Practical Sizes. CoRR abs/1908.02419 (2019) - [i14]Ameya D. Jagtap, Kenji Kawaguchi, George E. Karniadakis:
Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks. CoRR abs/1909.12228 (2019) - 2018
- [c5]Kenji Kawaguchi, Bo Xie, Le Song:
Deep Semi-Random Features for Nonlinear Function Approximation. AAAI 2018: 3382-3389 - [i13]Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar:
Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR abs/1801.00173 (2018) - [i12]Kenji Kawaguchi, Yoshua Bengio:
Generalization in Machine Learning via Analytical Learning Theory. CoRR abs/1802.07426 (2018) - [i11]Kenji Kawaguchi, Yoshua Bengio:
Depth with Nonlinearity Creates No Bad Local Minima in ResNets. CoRR abs/1810.09038 (2018) - [i10]Kenji Kawaguchi, Jiaoyang Huang, Leslie Pack Kaelbling:
Effect of Depth and Width on Local Minima in Deep Learning. CoRR abs/1811.08150 (2018) - 2017
- [i9]Haihao Lu, Kenji Kawaguchi:
Depth Creates No Bad Local Minima. CoRR abs/1702.08580 (2017) - [i8]Kenji Kawaguchi, Bo Xie, Le Song:
Deep Semi-Random Features for Nonlinear Function Approximation. CoRR abs/1702.08882 (2017) - [i7]Kenji Kawaguchi, Leslie Pack Kaelbling, Yoshua Bengio:
Generalization in Deep Learning. CoRR abs/1710.05468 (2017) - 2016
- [j2]Kenji Kawaguchi, Yu Maruyama, Xiaoyu Zheng:
Global Continuous Optimization with Error Bound and Fast Convergence. J. Artif. Intell. Res. 56: 153-195 (2016) - [c4]Kenji Kawaguchi:
Bounded Optimal Exploration in MDP. AAAI 2016: 1758-1764 - [c3]Kenji Kawaguchi:
Deep Learning without Poor Local Minima. NIPS 2016: 586-594 - [i6]Kenji Kawaguchi, Leslie Pack Kaelbling, Tomás Lozano-Pérez:
Bayesian Optimization with Exponential Convergence. CoRR abs/1604.01348 (2016) - [i5]Kenji Kawaguchi:
Bounded Optimal Exploration in MDP. CoRR abs/1604.01350 (2016) - [i4]Kenji Kawaguchi:
Deep Learning without Poor Local Minima. CoRR abs/1605.07110 (2016) - [i3]Kenji Kawaguchi, Yu Maruyama, Xiaoyu Zheng:
Global Continuous Optimization with Error Bound and Fast Convergence. CoRR abs/1607.04817 (2016) - [i2]Qianli Liao, Kenji Kawaguchi, Tomaso A. Poggio:
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning. CoRR abs/1610.06160 (2016) - 2015
- [j1]Xiaoyu Zheng, Hiroto Itoh, Kenji Kawaguchi, Hitoshi Tamaki, Yu Maruyama:
Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident. Reliab. Eng. Syst. Saf. 138: 253-262 (2015) - [c2]Kenji Kawaguchi, Leslie Pack Kaelbling, Tomás Lozano-Pérez:
Bayesian Optimization with Exponential Convergence. NIPS 2015: 2809-2817 - 2013
- [c1]Kenji Kawaguchi, Hiroshi Sato:
Prior-Free Exploration Bonus for and beyond Near Bayes-Optimal Behavior. IJCAI 2013: 1437-1443 - [i1]Kenji Kawaguchi, Mauricio Araya-López:
A Greedy Approximation of Bayesian Reinforcement Learning with Probably Optimistic Transition Model. CoRR abs/1303.3163 (2013)
Coauthor Index
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