default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDilip Krishnan
Person information
SPARQL queries 
🛈 Please note that only 51% of the records listed on this page have a DOI. Therefore, DOI-based queries can only provide partial results.
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
Books and Theses
- 2013
[b1]Dilip Krishnan:
Low-level Image Priors and Laplacian Preconditioners for Applications in Computer Graphics and Computational Photography. New York University, USA, 2013
Journal Articles
- 2023
- [j10]Apurva Kalia, Dilip Krishnan, Soha Hassoun
:
CSI: Contrastive data Stratification for Interaction prediction and its application to compound-protein interaction prediction. Bioinform. 39(8) (2023) - 2022
- [j9]Shlok Kumar Mishra, Anshul Shah, Ankan Bansal, Janit Anjaria, Abhyuday N. Jagannatha, Abhishek Sharma, David Jacobs, Dilip Krishnan:
Object-aware Cropping for Self-Supervised Learning. Trans. Mach. Learn. Res. 2022 (2022) - 2018
- [j8]Kanit Wongsuphasawat, Daniel Smilkov, James Wexler, Jimbo Wilson, Dandelion Mané, Doug Fritz, Dilip Krishnan, Fernanda B. Viégas, Martin Wattenberg:
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow. IEEE Trans. Vis. Comput. Graph. 24(1): 1-12 (2018) - 2013
- [j7]Dilip Krishnan, Raanan Fattal, Richard Szeliski:
Efficient preconditioning of laplacian matrices for computer graphics. ACM Trans. Graph. 32(4): 142:1-142:15 (2013) - 2011
- [j6]Dilip Krishnan, Richard Szeliski:
Multigrid and multilevel preconditioners for computational photography. ACM Trans. Graph. 30(6): 177 (2011) - 2009
- [j5]Dilip Krishnan, Quang Vinh Pham, Andy M. Yip:
A primal-dual active-set algorithm for bilaterally constrained total variation deblurring and piecewise constant Mumford-Shah segmentation problems. Adv. Comput. Math. 31(1-3): 237-266 (2009) - [j4]Dilip Krishnan, Rob Fergus:
Dark flash photography. ACM Trans. Graph. 28(3): 96 (2009) - 2007
- [j3]Dilip Krishnan, Ping Lin, Andy M. Yip:
A Primal-Dual Active-Set Method for Non-Negativity Constrained Total Variation Deblurring Problems. IEEE Trans. Image Process. 16(11): 2766-2777 (2007) - 1999
- [j2]Dilip Krishnan, Man-Nang Chong, Showbhik Kalra:
On the computational aspects of Gibbs-Markov random field modeling of missing-data in image sequences. IEEE Trans. Image Process. 8(8): 1139-1142 (1999) - 1998
- [j1]Man-Nang Chong, Dilip Krishnan:
An edge-preserving MRF model for the detection of missing data in image sequences. IEEE Signal Process. Lett. 5(4): 81-83 (1998)
Conference and Workshop Papers
- 2024
- [c37]Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian:
Scaling Laws of Synthetic Images for Model Training ... for Now. CVPR 2024: 7382-7392 - [c36]Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola:
Learning Vision from Models Rivals Learning Vision from Data. CVPR 2024: 15887-15898 - [c35]Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan:
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. ICLR 2024 - 2023
- [c34]Tianhong Li, Huiwen Chang, Shlok Kumar Mishra, Han Zhang, Dina Katabi, Dilip Krishnan:
MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis. CVPR 2023: 2142-2152 - [c33]Huiwen Chang, Han Zhang, Jarred Barber, Aaron Maschinot, José Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Patrick Murphy, William T. Freeman, Michael Rubinstein, Yuanzhen Li, Dilip Krishnan:
Muse: Text-To-Image Generation via Masked Generative Transformers. ICML 2023: 4055-4075 - [c32]Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian:
Improving CLIP Training with Language Rewrites. NeurIPS 2023 - [c31]Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, Daniel Castro Chin:
StyleDrop: Text-to-Image Synthesis of Any Style. NeurIPS 2023 - [c30]Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan:
StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. NeurIPS 2023 - 2022
- [c29]Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun:
Pyramid Adversarial Training Improves ViT Performance. CVPR 2022: 13409-13419 - 2021
- [c28]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML 2021: 10225-10235 - 2020
- [c27]Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola:
Rethinking Few-Shot Image Classification: A Good Embedding is All You Need? ECCV (14) 2020: 266-282 - [c26]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Multiview Coding. ECCV (11) 2020: 776-794 - [c25]Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio:
Fantastic Generalization Measures and Where to Find Them. ICLR 2020 - [c24]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Representation Distillation. ICLR 2020 - [c23]Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan:
Supervised Contrastive Learning. NeurIPS 2020 - [c22]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What Makes for Good Views for Contrastive Learning? NeurIPS 2020 - 2019
- [c21]Dilip Krishnan, Piotr Teterwak, Aaron Sarna, Aaron Maschinot, Ce Liu, David Belanger, William T. Freeman:
Boundless: Generative Adversarial Networks for Image Extension. ICCV 2019: 10520-10529 - [c20]Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio:
Predicting the Generalization Gap in Deep Networks with Margin Distributions. ICLR (Poster) 2019 - [c19]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. NeurIPS 2019: 13824-13833 - 2018
- [c18]Tali Dekel, Chuang Gan, Dilip Krishnan, Ce Liu, William T. Freeman:
Sparse, Smart Contours to Represent and Edit Images. CVPR 2018: 3511-3520 - [c17]Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio:
Large Margin Deep Networks for Classification. NeurIPS 2018: 850-860 - 2017
- [c16]Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan:
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CVPR 2017: 95-104 - [c15]Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman:
Synthesizing Normalized Faces from Facial Identity Features. CVPR 2017: 3386-3395 - [c14]Yaniv Ovadia, Yoni Halpern, Dilip Krishnan, Josh Livni, Daniel E. Newburger, Ryan Poplin, Tiantian Zha, D. Sculley:
Learning to Count Mosquitoes for the Sterile Insect Technique. KDD 2017: 1943-1949 - 2016
- [c13]Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan:
Domain Separation Networks. NIPS 2016: 343-351 - 2015
- [c12]Yichang Shih, Dilip Krishnan, Frédo Durand, William T. Freeman:
Reflection removal using ghosting cues. CVPR 2015: 3193-3201 - [c11]Daniel Zoran, Phillip Isola, Dilip Krishnan, William T. Freeman:
Learning Ordinal Relationships for Mid-Level Vision. ICCV 2015: 388-396 - 2014
- [c10]Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson:
Crisp Boundary Detection Using Pointwise Mutual Information. ECCV (3) 2014: 799-814 - [c9]Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman:
Shape and Illumination from Shading using the Generic Viewpoint Assumption. NIPS 2014: 226-234 - 2013
- [c8]David Eigen, Dilip Krishnan, Rob Fergus:
Restoring an Image Taken through a Window Covered with Dirt or Rain. ICCV 2013: 633-640 - 2011
- [c7]Dilip Krishnan, Terence Tay, Rob Fergus:
Blind deconvolution using a normalized sparsity measure. CVPR 2011: 233-240 - 2010
- [c6]Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus:
Deconvolutional networks. CVPR 2010: 2528-2535 - 2009
- [c5]Dilip Krishnan, Rob Fergus:
Fast Image Deconvolution using Hyper-Laplacian Priors. NIPS 2009: 1033-1041 - 1999
- [c4]Showbhik Kalra, Dilip Krishnan, Man-Nang Chong:
A MRF Model Based Scheme for Accurate Detection and Adaptive Interpolation of Missing Data in Highly Corrupted Image Sequences. ICIP (2) 1999: 890-893 - 1997
- [c3]Showbhik Kalra, Man-Nang Chong, Dilip Krishnan:
A new auto-regressive (AR) model-based algorithm for motion picture restoration. ICASSP 1997: 2557-2560 - [c2]Man-Nang Chong, P. Liu, Wooi Boon Goh, Dilip Krishnan:
A new spatio-temporal MRF model for the detection of missing data in image sequences. ICASSP 1997: 2977-2980 - 1996
- [c1]Wooi Boon Goh, Man-Nang Chong, Showbhik Kalra, Dilip Krishnan:
Bi-directional 3D auto-regressive model approach to motion picture restoration. ICASSP 1996: 2275-2278
Informal and Other Publications
- 2023
- [i34]Huiwen Chang, Han Zhang, Jarred Barber, Aaron Maschinot, José Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T. Freeman, Michael Rubinstein, Yuanzhen Li, Dilip Krishnan:
Muse: Text-To-Image Generation via Masked Generative Transformers. CoRR abs/2301.00704 (2023) - [i33]Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan:
Steerable Equivariant Representation Learning. CoRR abs/2302.11349 (2023) - [i32]Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian:
Improving CLIP Training with Language Rewrites. CoRR abs/2305.20088 (2023) - [i31]Kihyuk Sohn, Nataniel Ruiz, Kimin Lee, Daniel Castro Chin, Irina Blok, Huiwen Chang, Jarred Barber, Lu Jiang, Glenn Entis, Yuanzhen Li, Yuan Hao, Irfan Essa, Michael Rubinstein, Dilip Krishnan:
StyleDrop: Text-to-Image Generation in Any Style. CoRR abs/2306.00983 (2023) - [i30]Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan:
StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. CoRR abs/2306.00984 (2023) - [i29]Cyrus Rashtchian, Charles Herrmann, Chun-Sung Ferng, Ayan Chakrabarti, Dilip Krishnan, Deqing Sun, Da-Cheng Juan, Andrew Tomkins:
Substance or Style: What Does Your Image Embedding Know? CoRR abs/2307.05610 (2023) - [i28]Tianhong Li, Sangnie Bhardwaj, Yonglong Tian, Han Zhang, Jarred Barber, Dina Katabi, Guillaume Lajoie, Huiwen Chang, Dilip Krishnan:
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency. CoRR abs/2310.03734 (2023) - [i27]Kaifeng Chen, Daniel Salz, Huiwen Chang, Kihyuk Sohn, Dilip Krishnan, Mojtaba Seyedhosseini:
Improve Supervised Representation Learning with Masked Image Modeling. CoRR abs/2312.00950 (2023) - [i26]Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian:
Scaling Laws of Synthetic Images for Model Training ... for Now. CoRR abs/2312.04567 (2023) - [i25]Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola:
Learning Vision from Models Rivals Learning Vision from Data. CoRR abs/2312.17742 (2023) - 2022
- [i24]Shlok Mishra, Joshua Robinson, Huiwen Chang, David Jacobs, Aaron Sarna, Aaron Maschinot, Dilip Krishnan:
A simple, efficient and scalable contrastive masked autoencoder for learning visual representations. CoRR abs/2210.16870 (2022) - [i23]Tianhong Li, Huiwen Chang, Shlok Kumar Mishra, Han Zhang, Dina Katabi, Dilip Krishnan:
MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis. CoRR abs/2211.09117 (2022) - 2021
- [i22]Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer:
Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR abs/2103.07470 (2021) - [i21]Andrea Burns, Aaron Sarna, Dilip Krishnan, Aaron Maschinot:
Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions. CoRR abs/2108.06613 (2021) - [i20]Apurva Kalia, Dilip Krishnan, Soha Hassoun:
Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction. CoRR abs/2111.09467 (2021) - [i19]Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun:
Pyramid Adversarial Training Improves ViT Performance. CoRR abs/2111.15121 (2021) - [i18]Shlok Mishra, Anshul Shah, Ankan Bansal, Abhyuday Jagannatha, Abhishek Sharma, David Jacobs, Dilip Krishnan:
Object-Aware Cropping for Self-Supervised Learning. CoRR abs/2112.00319 (2021) - 2020
- [i17]Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola:
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need? CoRR abs/2003.11539 (2020) - [i16]Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan:
Supervised Contrastive Learning. CoRR abs/2004.11362 (2020) - [i15]Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola:
What makes for good views for contrastive learning. CoRR abs/2005.10243 (2020) - 2019
- [i14]Vighnesh Birodkar, Hossein Mobahi, Dilip Krishnan, Samy Bengio:
A Closed-Form Learned Pooling for Deep Classification Networks. CoRR abs/1906.03808 (2019) - [i13]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Multiview Coding. CoRR abs/1906.05849 (2019) - [i12]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. CoRR abs/1907.02610 (2019) - [i11]Piotr Teterwak, Aaron Sarna, Dilip Krishnan, Aaron Maschinot, David Belanger, Ce Liu, William T. Freeman:
Boundless: Generative Adversarial Networks for Image Extension. CoRR abs/1908.07007 (2019) - [i10]Yonglong Tian, Dilip Krishnan, Phillip Isola:
Contrastive Representation Distillation. CoRR abs/1910.10699 (2019) - [i9]Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio:
Fantastic Generalization Measures and Where to Find Them. CoRR abs/1912.02178 (2019) - 2018
- [i8]Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio:
Large Margin Deep Networks for Classification. CoRR abs/1803.05598 (2018) - [i7]Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio:
Predicting the Generalization Gap in Deep Networks with Margin Distributions. CoRR abs/1810.00113 (2018) - 2017
- [i6]Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman:
Face Synthesis from Facial Identity Features. CoRR abs/1701.04851 (2017) - [i5]Tali Dekel, Chuang Gan, Dilip Krishnan, Ce Liu, William T. Freeman:
Smart, Sparse Contours to Represent and Edit Images. CoRR abs/1712.08232 (2017) - 2016
- [i4]Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan:
Domain Separation Networks. CoRR abs/1608.06019 (2016) - [i3]Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan:
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CoRR abs/1612.05424 (2016) - 2015
- [i2]Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson:
Learning visual groups from co-occurrences in space and time. CoRR abs/1511.06811 (2015) - 2013
- [i1]Dilip Krishnan, Joan Bruna, Rob Fergus:
Blind Deconvolution with Re-weighted Sparsity Promotion. CoRR abs/1311.4029 (2013)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 01:24 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
