Dilip Krishnan

Publication Activity (10 Years)

Years Active: 1996-2024
Publications (10 Years): 58

Top Topics

Pointwise Mutual Information

Salient Contours

Visual Representations

Image Generation

Top Venues

Publications

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)
Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola
Learning Vision from Models Rivals Learning Vision from Data. CoRR (2023)
Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian
Scaling Laws of Synthetic Images for Model Training ... for Now. CoRR (2023)
Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan
StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners. CoRR (2023)
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 (2023)
Kaifeng Chen, Daniel Salz, Huiwen Chang, Kihyuk Sohn, Dilip Krishnan, Mojtaba Seyedhosseini
Improve Supervised Representation Learning with Masked Image Modeling. CoRR (2023)
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)
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 (2023)
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)
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)
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)
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 (2023)
Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan
Steerable Equivariant Representation Learning. CoRR (2023)
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)
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian
Improving CLIP Training with Language Rewrites. CoRR (2023)
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian
Improving CLIP Training with Language Rewrites. NeurIPS (2023)
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 (2023)
Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun
Pyramid Adversarial Training Improves ViT Performance. CVPR (2022)
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 (2022)
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 (2022)
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)
Apurva Kalia, Dilip Krishnan, Soha Hassoun
Contrastive Multiview Coding for Enzyme-Substrate Interaction Prediction. CoRR (2021)
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML (2021)
Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun
Pyramid Adversarial Training Improves ViT Performance. CoRR (2021)
Andrea Burns, Aaron Sarna, Dilip Krishnan, Aaron Maschinot
Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions. CoRR (2021)
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR (2021)
Shlok Mishra, Anshul Shah, Ankan Bansal, Abhyuday Jagannatha, Abhishek Sharma, David W. Jacobs, Dilip Krishnan
Object-Aware Cropping for Self-Supervised Learning. CoRR (2021)
Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need? CoRR (2020)
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
Fantastic Generalization Measures and Where to Find Them. ICLR (2020)
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan
Supervised Contrastive Learning. NeurIPS (2020)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What Makes for Good Views for Contrastive Learning? NeurIPS (2020)
Yonglong Tian, Dilip Krishnan, Phillip Isola
Contrastive Multiview Coding. ECCV (11) (2020)
Yonglong Tian, Dilip Krishnan, Phillip Isola
Contrastive Representation Distillation. ICLR (2020)
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan
Supervised Contrastive Learning. CoRR (2020)
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)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What makes for good views for contrastive learning. CoRR (2020)
Dilip Krishnan, Piotr Teterwak, Aaron Sarna, Aaron Maschinot, Ce Liu, David Belanger, William T. Freeman
Boundless: Generative Adversarial Networks for Image Extension. ICCV (2019)
Piotr Teterwak, Aaron Sarna, Dilip Krishnan, Aaron Maschinot, David Belanger, Ce Liu, William T. Freeman
Boundless: Generative Adversarial Networks for Image Extension. CoRR (2019)
Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio
Predicting the Generalization Gap in Deep Networks with Margin Distributions. ICLR (Poster) (2019)
Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio
Fantastic Generalization Measures and Where to Find Them. CoRR (2019)
Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli
Adversarial Robustness through Local Linearization. CoRR (2019)
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)
Yonglong Tian, Dilip Krishnan, Phillip Isola
Contrastive Representation Distillation. CoRR (2019)
Vighnesh Birodkar, Hossein Mobahi, Dilip Krishnan, Samy Bengio
A Closed-Form Learned Pooling for Deep Classification Networks. CoRR (2019)
Yonglong Tian, Dilip Krishnan, Phillip Isola
Contrastive Multiview Coding. CoRR (2019)
Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio
Large Margin Deep Networks for Classification. NeurIPS (2018)
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) (2018)
Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi, Kevin Regan, Samy Bengio
Large Margin Deep Networks for Classification. CoRR (2018)
Yiding Jiang, Dilip Krishnan, Hossein Mobahi, Samy Bengio
Predicting the Generalization Gap in Deep Networks with Margin Distributions. CoRR (2018)
Tali Dekel, Chuang Gan, Dilip Krishnan, Ce Liu, William T. Freeman
Sparse, Smart Contours to Represent and Edit Images. CVPR (2018)
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CVPR (2017)
Tali Dekel, Chuang Gan, Dilip Krishnan, Ce Liu, William T. Freeman
Smart, Sparse Contours to Represent and Edit Images. CoRR (2017)
Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman
Face Synthesis from Facial Identity Features. CoRR (2017)
Yaniv Ovadia, Yoni Halpern, Dilip Krishnan, Josh Livni, Daniel Newburger, Ryan Poplin, Tiantian Zha, D. Sculley
Learning to Count Mosquitoes for the Sterile Insect Technique. KDD (2017)
Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman
Synthesizing Normalized Faces from Facial Identity Features. CVPR (2017)
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
Domain Separation Networks. NIPS (2016)
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, Dumitru Erhan
Domain Separation Networks. CoRR (2016)
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CoRR (2016)
Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson
Learning visual groups from co-occurrences in space and time. CoRR (2015)
Daniel Zoran, Phillip Isola, Dilip Krishnan, William T. Freeman
Learning Ordinal Relationships for Mid-Level Vision. ICCV (2015)
Yi-Chang Shih, Dilip Krishnan, Frédo Durand, William T. Freeman
Reflection removal using ghosting cues. CVPR (2015)
Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson
Crisp Boundary Detection Using Pointwise Mutual Information. ECCV (3) (2014)
Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman
Shape and Illumination from Shading using the Generic Viewpoint Assumption. NIPS (2014)
Dilip Krishnan, Raanan Fattal, Richard Szeliski
Efficient preconditioning of laplacian matrices for computer graphics. ACM Trans. Graph. 32 (4) (2013)
David Eigen, Dilip Krishnan, Rob Fergus
Restoring an Image Taken through a Window Covered with Dirt or Rain. ICCV (2013)
Dilip Krishnan, Joan Bruna, Rob Fergus
Blind Deconvolution with Re-weighted Sparsity Promotion. CoRR (2013)
Dilip Krishnan, Terence Tay, Rob Fergus
Blind deconvolution using a normalized sparsity measure. CVPR (2011)
Dilip Krishnan, Richard Szeliski
Multigrid and multilevel preconditioners for computational photography. ACM Trans. Graph. 30 (6) (2011)
Matthew D. Zeiler, Dilip Krishnan, Graham W. Taylor, Robert Fergus
Deconvolutional networks. CVPR (2010)
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) (2009)
Dilip Krishnan, Rob Fergus
Fast Image Deconvolution using Hyper-Laplacian Priors. NIPS (2009)
Dilip Krishnan, Rob Fergus
Dark flash photography. ACM Trans. Graph. 28 (3) (2009)
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) (2007)
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) (1999)
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)
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) (1998)
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)
Showbhik Kalra, Man-Nang Chong, Dilip Krishnan
A new auto-regressive (AR) model-based algorithm for motion picture restoration. ICASSP (1997)
Wooi Boon Goh, Man-Nang Chong, Showbhik Kalra, Dilip Krishnan
Bi-directional 3D auto-regressive model approach to motion picture restoration. ICASSP (1996)