Simon Kornblith

According to our database, Simon Kornblith authored at least 55 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

When Does Perceptual Alignment Benefit Vision Representations?

Shobhita Sundaram, Stephanie Fu, Lukas Muttenthaler, Netanel Y. Tamir, Lucy Chai, Simon Kornblith, Trevor Darrell, Phillip Isola

CoRR, 2024

Aligning Machine and Human Visual Representations across Abstraction Levels.

Lukas Muttenthaler, Klaus Greff, Frieda Born, Bernhard Spitzer, Simon Kornblith, Michael C. Mozer, Klaus-Robert Müller, Thomas Unterthiner, Andrew K. Lampinen

CoRR, 2024

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability.

Jiri Hron, Laura Culp, Gamaleldin F. Elsayed, Rosanne Liu, Ben Adlam, Maxwell L. Bileschi, Bernd Bohnet, JD Co-Reyes, Noah Fiedel, C. Daniel Freeman, Izzeddin Gur, Kathleen Kenealy, Jaehoon Lee, Peter J. Liu, Gaurav Mishra, Igor Mordatch, Azade Nova, Roman Novak, Aaron Parisi, Jeffrey Pennington, Alex Rizkowsky, Isabelle Simpson, Hanie Sedghi, Jascha Sohl-Dickstein, Kevin Swersky, Sharad Vikram, Tris Warkentin, Lechao Xiao, Kelvin Xu, Jasper Snoek, Simon Kornblith

CoRR, 2024

Small-scale proxies for large-scale Transformer training instabilities.

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Synthetic Data from Diffusion Models Improves ImageNet Classification.

Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, David J. Fleet

Trans. Mach. Learn. Res., 2023

Neither hype nor gloom do DNNs justice.

Felix A. Wichmann, Simon Kornblith, Robert Geirhos

CoRR, 2023

Probing clustering in neural network representations.

Thao Nguyen, Simon Kornblith

CoRR, 2023

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5?

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

CoRR, 2023

Getting aligned on representational alignment.

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

CoRR, 2023

Replacing softmax with ReLU in Vision Transformers.

Mitchell Wortsman, Jaehoon Lee, Justin Gilmer, Simon Kornblith

CoRR, 2023

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

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

CoRR, 2023

Towards Generalist Biomedical AI.

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

CoRR, 2023

Improving neural network representations using human similarity judgments.

Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Does progress on ImageNet transfer to real-world datasets?

Alex Fang, Simon Kornblith, Ludwig Schmidt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Relationship Between Explanation and Prediction: A Causal View.

Amir-Hossein Karimi, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, Been Kim

Proceedings of the International Conference on Machine Learning, 2023

Scaling Forward Gradient With Local Losses.

Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Human alignment of neural network representations.

Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Guiding image captioning models toward more specific captions.

Simon Kornblith, Lala Li, Zirui Wang, Thao Nguyen

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Hyperbolic Contrastive Learning for Visual Representations beyond Objects.

Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

FlexiViT: One Model for All Patch Sizes.

Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Interpretability of artificial neural network models in artificial intelligence versus neuroscience.

Kohitij Kar, Simon Kornblith, Evelina Fedorenko

Nat. Mac. Intell., December, 2022

On the Origins of the Block Structure Phenomenon in Neural Network Representations.

Thao Nguyen, Maithra Raghu, Simon Kornblith

Trans. Mach. Learn. Res., 2022

Decoder Denoising Pretraining for Semantic Segmentation.

Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi

Trans. Mach. Learn. Res., 2022

Gaussian-Bernoulli RBMs Without Tears.

Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet, Geoffrey E. Hinton

CoRR, 2022

Improving Dense Contrastive Learning with Dense Negative Pairs.

Berk Iskender, Zhenlin Xu, Simon Kornblith, Enhung Chu, Maryam Khademi

CoRR, 2022

Robust and Efficient Medical Imaging with Self-Supervision.

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

CoRR, 2022

Boosting Contrastive Self-Supervised Learning with False Negative Cancellation.

Tri Huynh, Simon Kornblith, Matthew R. Walter, Michael Maire, Maryam Khademi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Patching open-vocabulary models by interpolating weights.

Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, Ludwig Schmidt

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

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

Proceedings of the International Conference on Machine Learning, 2022

A Study on Self-Supervised Object Detection Pretraining.

Trung Dang, Simon Kornblith, Huy Thong Nguyen, Peter Chin, Maryam Khademi

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Robust fine-tuning of zero-shot models.

Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, Ludwig Schmidt

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Denoising Pretraining for Semantic Segmentation.

Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Generalized Shape Metrics on Neural Representations.

Alex H. Williams, Erin Kunz, Simon Kornblith, Scott W. Linderman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Do Vision Transformers See Like Convolutional Neural Networks?

Maithra Raghu, Thomas Unterthiner, Simon Kornblith, Chiyuan Zhang, Alexey Dosovitskiy

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-learning to Improve Pre-training.

Aniruddh Raghu, Jonathan Lorraine, Simon Kornblith, Matthew McDermott, David Duvenaud

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Why Do Better Loss Functions Lead to Less Transferable Features?

Simon Kornblith, Ting Chen, Honglak Lee, Mohammad Norouzi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Generalised Lipschitz Regularisation Equals Distributional Robustness.

Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith

Proceedings of the 38th International Conference on Machine Learning, 2021

Teaching with Commentaries.

Aniruddh Raghu, Maithra Raghu, Simon Kornblith, David Duvenaud, Geoffrey E. Hinton

Proceedings of the 9th International Conference on Learning Representations, 2021

Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth.

Thao Nguyen, Maithra Raghu, Simon Kornblith

Proceedings of the 9th International Conference on Learning Representations, 2021

Big Self-Supervised Models Advance Medical Image Classification.

Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

MIST: Multiple Instance Spatial Transformer.

Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi, Kwang Moo Yi

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

What's in a Loss Function for Image Classification?

Simon Kornblith, Honglak Lee, Ting Chen, Mohammad Norouzi

CoRR, 2020

Subclass Distillation.

Rafael Müller, Simon Kornblith, Geoffrey E. Hinton

CoRR, 2020

The Origins and Prevalence of Texture Bias in Convolutional Neural Networks.

Katherine L. Hermann, Ting Chen, Simon Kornblith

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Big Self-Supervised Models are Strong Semi-Supervised Learners.

Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Revisiting Spatial Invariance with Low-Rank Local Connectivity.

Gamaleldin F. Elsayed, Prajit Ramachandran, Jonathon Shlens, Simon Kornblith

Proceedings of the 37th International Conference on Machine Learning, 2020

A Simple Framework for Contrastive Learning of Visual Representations.

Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey E. Hinton

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Exploring the Origins and Prevalence of Texture Bias in Convolutional Neural Networks.

Katherine L. Hermann, Simon Kornblith

CoRR, 2019

Cerberus: A Multi-headed Derenderer.

Boyang Deng, Simon Kornblith, Geoffrey E. Hinton

CoRR, 2019

When does label smoothing help?

Rafael Müller, Simon Kornblith, Geoffrey E. Hinton

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Saccader: Improving Accuracy of Hard Attention Models for Vision.

Gamaleldin F. Elsayed, Simon Kornblith, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Similarity of Neural Network Representations Revisited.

Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey E. Hinton

Proceedings of the 36th International Conference on Machine Learning, 2019

Do Better ImageNet Models Transfer Better?

Simon Kornblith, Jonathon Shlens, Quoc V. Le

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Domain Adaptive Transfer Learning with Specialist Models.

Jiquan Ngiam, Daiyi Peng, Vijay Vasudevan, Simon Kornblith, Quoc V. Le, Ruoming Pang

CoRR, 2018

Lipschitz Networks and Distributional Robustness.

Zac Cranko, Simon Kornblith, Zhan Shi, Richard Nock

CoRR, 2018