Simon Kornblith

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 82

Top Topics

Visual Representation

Diffusion Models

Top Venues

Publications

Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie E. Everett, Alexander A. Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith
Small-scale proxies for large-scale Transformer training instabilities. ICLR (2024)
Mitchell Wortsman, Jaehoon Lee, Justin Gilmer, Simon Kornblith
Replacing softmax with ReLU in Vision Transformers. CoRR (2023)
Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
Scaling Forward Gradient With Local Losses. ICLR (2023)
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
FlexiViT: One Model for All Patch Sizes. CVPR (2023)
Alex Fang, Simon Kornblith, Ludwig Schmidt
Does progress on ImageNet transfer to real-world datasets? CoRR (2023)
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
Improving neural network representations using human similarity judgments. CoRR (2023)
Alex Fang, Simon Kornblith, Ludwig Schmidt
Does progress on ImageNet transfer to real-world datasets? NeurIPS (2023)
Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno, Ira Ktena, Basil Mustafa, Aakanksha Chowdhery, Yun Liu, Simon Kornblith, David J. Fleet, Philip Andrew Mansfield, Sushant Prakash, Renee Wong, Sunny Virmani, Christopher Semturs, S. Sara Mahdavi, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, Vivek Natarajan
Towards Generalist Biomedical AI. CoRR (2023)
Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, David J. Fleet
Synthetic Data from Diffusion Models Improves ImageNet Classification. Trans. Mach. Learn. Res. 2023 (2023)
Felix A. Wichmann, Simon Kornblith, Robert Geirhos
Neither hype nor gloom do DNNs justice. CoRR (2023)
Mitchell Wortsman, Peter J. Liu, Lechao Xiao, Katie Everett, Alex Alemi, Ben Adlam, John D. Co-Reyes, Izzeddin Gur, Abhishek Kumar, Roman Novak, Jeffrey Pennington, Jascha Sohl-Dickstein, Kelvin Xu, Jaehoon Lee, Justin Gilmer, Simon Kornblith
Small-scale proxies for large-scale Transformer training instabilities. CoRR (2023)
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
Improving neural network representations using human similarity judgments. NeurIPS (2023)
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths
Getting aligned on representational alignment. CoRR (2023)
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, Ludwig Schmidt
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. CoRR (2023)
Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, David J. Fleet
Synthetic Data from Diffusion Models Improves ImageNet Classification. CoRR (2023)
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
Human alignment of neural network representations. ICLR (2023)
Simon Kornblith, Lala Li, Zirui Wang, Thao Nguyen
Guiding image captioning models toward more specific captions. ICCV (2023)
Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
On the Relationship Between Explanation and Prediction: A Causal View. ICML (2023)
Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CVPR (2023)
Thao Nguyen, Simon Kornblith
Probing clustering in neural network representations. CoRR (2023)
Simon Kornblith, Lala Li, Zirui Wang, Thao Nguyen
Guiding Image Captioning Models Toward More Specific Captions. CoRR (2023)
C. Daniel Freeman, Laura Culp, Aaron Parisi, Maxwell L. Bileschi, Gamaleldin F. Elsayed, Alex Rizkowsky, Isabelle Simpson, Alex Alemi, Azade Nova, Ben Adlam, Bernd Bohnet, Gaurav Mishra, Hanie Sedghi, Igor Mordatch, Izzeddin Gur, Jaehoon Lee, John D. Co-Reyes, Jeffrey Pennington, Kelvin Xu, Kevin Swersky, Kshiteej Mahajan, Lechao Xiao, Rosanne Liu, Simon Kornblith, Noah Constant, Peter J. Liu, Roman Novak, Yundi Qian, Noah Fiedel, Jascha Sohl-Dickstein
Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? CoRR (2023)
Shekoofeh Azizi, Laura Culp, Jan Freyberg, Basil Mustafa, Sebastien Baur, Simon Kornblith, Ting Chen, Patricia MacWilliams, S. Sara Mahdavi, Ellery Wulczyn, Boris Babenko, Megan Wilson, Aaron Loh, Po-Hsuan Cameron Chen, Yuan Liu, Pinal Bavishi, Scott Mayer McKinney, Jim Winkens, Abhijit Guha Roy, Zachary Beaver, Fiona Ryan, Justin Krogue, Mozziyar Etemadi, Umesh Telang, Yun Liu, Lily Peng, Gregory S. Corrado, Dale R. Webster, David J. Fleet, Geoffrey E. Hinton, Neil Houlsby, Alan Karthikesalingam, Mohammad Norouzi, Vivek Natarajan
Robust and Efficient Medical Imaging with Self-Supervision. CoRR (2022)
Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, Maryam Khademi
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation. WACV (2022)
Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi
Decoder Denoising Pretraining for Semantic Segmentation. CoRR (2022)
Trung Dang, Simon Kornblith, Huy Thong Nguyen, Peter Chin, Maryam Khademi
A Study on Self-Supervised Object Detection Pretraining. CoRR (2022)
Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt
Robust fine-tuning of zero-shot models. CVPR (2022)
Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet, Geoffrey E. Hinton
Gaussian-Bernoulli RBMs Without Tears. CoRR (2022)
Mitchell Wortsman, Gabriel Ilharco, Samir Ya Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. ICML (2022)
Thao Nguyen, Maithra Raghu, Simon Kornblith
On the Origins of the Block Structure Phenomenon in Neural Network Representations. CoRR (2022)
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
Human alignment of neural network representations. CoRR (2022)
Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton
Scaling Forward Gradient With Local Losses. CoRR (2022)
Berk Iskender, Zhenlin Xu, Simon Kornblith, Enhung Chu, Maryam Khademi
Improving Dense Contrastive Learning with Dense Negative Pairs. CoRR (2022)
Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi
Denoising Pretraining for Semantic Segmentation. CVPR Workshops (2022)
Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CoRR (2022)
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt
Patching open-vocabulary models by interpolating weights. NeurIPS (2022)
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt
Patching open-vocabulary models by interpolating weights. CoRR (2022)
Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi
Decoder Denoising Pretraining for Semantic Segmentation. Trans. Mach. Learn. Res. 2022 (2022)
Trung Dang, Simon Kornblith, Huy Thong Nguyen, Peter Chin, Maryam Khademi
A Study on Self-Supervised Object Detection Pretraining. ECCV Workshops (4) (2022)
Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic
FlexiViT: One Model for All Patch Sizes. CoRR (2022)
Kohitij Kar, Simon Kornblith, Evelina Fedorenko
Interpretability of artificial neural network models in artificial intelligence versus neuroscience. Nat. Mac. Intell. 4 (12) (2022)
Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. CoRR (2022)
Thao Nguyen, Maithra Raghu, Simon Kornblith
On the Origins of the Block Structure Phenomenon in Neural Network Representations. Trans. Mach. Learn. Res. 2022 (2022)
Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim
On the Relationship Between Explanation and Prediction: A Causal View. CoRR (2022)
Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi
Big Self-Supervised Models Advance Medical Image Classification. ICCV (2021)
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy
Do Vision Transformers See Like Convolutional Neural Networks? CoRR (2021)
Thao Nguyen, Maithra Raghu, Simon Kornblith
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth. ICLR (2021)
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton
Teaching with Commentaries. ICLR (2021)
Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy
Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS (2021)
Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman
Generalized Shape Metrics on Neural Representations. CoRR (2021)
Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud
Meta-Learning to Improve Pre-Training. CoRR (2021)
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Generalised Lipschitz Regularisation Equals Distributional Robustness. ICML (2021)
Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman
Generalized Shape Metrics on Neural Representations. NeurIPS (2021)
Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi, Kwang Moo Yi
MIST: Multiple Instance Spatial Transformer. CVPR (2021)
Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi
Big Self-Supervised Models Advance Medical Image Classification. CoRR (2021)
Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi
Why Do Better Loss Functions Lead to Less Transferable Features? NeurIPS (2021)
Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud
Meta-learning to Improve Pre-training. NeurIPS (2021)
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton
Big Self-Supervised Models are Strong Semi-Supervised Learners. NeurIPS (2020)
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton
A Simple Framework for Contrastive Learning of Visual Representations. ICML (2020)
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith
Generalised Lipschitz Regularisation Equals Distributional Robustness. CoRR (2020)
Thao Nguyen, Maithra Raghu, Simon Kornblith
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth. CoRR (2020)
Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi
What's in a Loss Function for Image Classification? CoRR (2020)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
Subclass Distillation. CoRR (2020)
Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith
Revisiting Spatial Invariance with Low-Rank Local Connectivity. CoRR (2020)
Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, Maryam Khademi
Boosting Contrastive Self-Supervised Learning with False Negative Cancellation. CoRR (2020)
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton
Big Self-Supervised Models are Strong Semi-Supervised Learners. CoRR (2020)
Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith
Revisiting Spatial Invariance with Low-Rank Local Connectivity. ICML (2020)
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton
A Simple Framework for Contrastive Learning of Visual Representations. CoRR (2020)
Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton
Teaching with Commentaries. CoRR (2020)
Katherine L. Hermann, Ting Chen, Simon Kornblith
The Origins and Prevalence of Texture Bias in Convolutional Neural Networks. NeurIPS (2020)
Katherine L. Hermann, Simon Kornblith
Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks. CoRR (2019)
Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le
Saccader: Improving Accuracy of Hard Attention Models for Vision. NeurIPS (2019)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
When Does Label Smoothing Help? CoRR (2019)
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
Similarity of Neural Network Representations Revisited. CoRR (2019)
Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton
Similarity of Neural Network Representations Revisited. ICML (2019)
Simon Kornblith, Jonathon Shlens, Quoc V. Le
Do Better ImageNet Models Transfer Better? CVPR (2019)
Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le
Saccader: Improving Accuracy of Hard Attention Models for Vision. CoRR (2019)
Rafael Müller, Simon Kornblith, Geoffrey E. Hinton
When does label smoothing help? NeurIPS (2019)
Boyang Deng, Simon Kornblith, Geoffrey E. Hinton
Cerberus: A Multi-headed Derenderer. CoRR (2019)
Jiquan Ngiam, Daiyi Peng, Vijay Vasudevan, Simon Kornblith, Quoc V. Le, Ruoming Pang
Domain Adaptive Transfer Learning with Specialist Models. CoRR (2018)
Simon Kornblith, Jonathon Shlens, Quoc V. Le
Do Better ImageNet Models Transfer Better? CoRR (2018)
Zac Cranko, Simon Kornblith, Zhan Shi, Richard Nock
Lipschitz Networks and Distributional Robustness. CoRR (2018)