Phillip Isola

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 136

Top Venues

CoRR

NeurIPS

CVPR

ICLR

Publications

Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola
The Platonic Representation Hypothesis. CoRR (2024)
Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola, Pulkit Agrawal
Training Neural Networks from Scratch with Parallel Low-Rank Adapters. CoRR (2024)
Pratyusha Sharma, Tamar Rott Shaham, Manel Baradad, Stephanie Fu, Adrián Rodríguez-Muñoz, Shivam Duggal, Phillip Isola, Antonio Torralba
A Vision Check-up for Language Models. CoRR (2024)
Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein
Scalable Optimization in the Modular Norm. CoRR (2024)
Jerry Ngo, Swami Sankaranarayanan, Phillip Isola
Is CLIP Fooled by Optical Illusions? Tiny Papers @ ICLR (2023)
Joseph Suarez, David Bloomin, Kyoung Whan Choe, Hao Xiang Li, Ryan Sullivan, Nishaanth Kanna, Daniel Scott, Rose S. Shuman, Herbie Bradley, Louis Castricato, Phillip Isola, Chenghui Yu, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. NeurIPS (2023)
Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola
The Low-Rank Simplicity Bias in Deep Networks. Trans. Mach. Learn. Res. 2023 (2023)
Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. ICML (2023)
Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely
Persistent Nature: A Generative Model of Unbounded 3D Worlds. CoRR (2023)
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)
Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data. NeurIPS (2023)
Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. CoRR (2023)
Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. CoRR (2023)
William Shen, Ge Yang, Alan Yu, Jansen Wong, Leslie Pack Kaelbling, Phillip Isola
Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation. CoRL (2023)
Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely
Persistent Nature: A Generative Model of Unbounded 3D Worlds. CVPR (2023)
William Shen, Ge Yang, Alan Yu, Jansen Wong, Leslie Pack Kaelbling, Phillip Isola
Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation. CoRR (2023)
Kevin Frans, Phillip Isola
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions. ICLR (2023)
Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola
DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data. CoRR (2023)
Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. AAMAS (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)
Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. ICML (2023)
Sangnie Bhardwaj, Willie McClinton, Tongzhou Wang, Guillaume Lajoie, Chen Sun, Phillip Isola, Dilip Krishnan
Steerable Equivariant Representation Learning. CoRR (2023)
Joseph Suárez, Phillip Isola, Kyoung Whan Choe, David Bloomin, Hao Xiang Li, Nikhil Pinnaparaju, Nishaanth Kanna, Daniel Scott, Ryan Sullivan, Rose S. Shuman, Lucas de Alcântara, Herbie Bradley, Louis Castricato, Kirsty You, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. CoRR (2023)
Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning. CoRR (2023)
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian
Improving CLIP Training with Language Rewrites. CoRR (2023)
Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, Bingcheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade. CoRR (2023)
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian
Improving CLIP Training with Language Rewrites. NeurIPS (2023)
Bowen Pan, Rameswar Panda, SouYoung Jin, Rogério Feris, Aude Oliva, Phillip Isola, Yoon Kim
LangNav: Language as a Perceptual Representation for Navigation. CoRR (2023)
Miriam Cha, Gregory Angelides, Mark Hamilton, Andy Soszynski, Brandon Swenson, Nathaniel Maidel, Phillip Isola, Taylor Perron, Bill Freeman
MultiEarth 2023 - Multimodal Learning for Earth and Environment Workshop and Challenge. CoRR (2023)
Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang
Any-resolution Training for High-resolution Image Synthesis. CoRR (2022)
Caroline Chan, Frédo Durand, Phillip Isola
Learning to generate line drawings that convey geometry and semantics. CoRR (2022)
Manel Baradad, Chun-Fu Richard Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola
Procedural Image Programs for Representation Learning. NeurIPS (2022)
Caroline Chan, Frédo Durand, Phillip Isola
Learning to generate line drawings that convey geometry and semantics. CVPR (2022)
Kevin Frans, Phillip Isola
Powderworld: A Platform for Understanding Generalization via Rich Task Distributions. CoRR (2022)
Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum
Noisy Agents: Self-supervised Exploration by Predicting Auditory Events. IROS (2022)
Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola
Semantic uncertainty intervals for disentangled latent spaces. NeurIPS (2022)
Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
Denoised MDPs: Learning World Models Better Than the World Itself. CoRR (2022)
Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez, Phillip Isola
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. CoRR (2022)
Tongzhou Wang, Phillip Isola
On the Learning and Learnablity of Quasimetrics. CoRR (2022)
Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola
MIRA: Mental Imagery for Robotic Affordances. CoRL (2022)
Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba
Totems: Physical Objects for Verifying Visual Integrity. CoRR (2022)
Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Ser-Nam Lim, Phillip Isola, Antonio Torralba
Totems: Physical Objects for Verifying Visual Integrity. ECCV (14) (2022)
Tongzhou Wang, Phillip Isola
Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings. CoRR (2022)
Tongzhou Wang, Phillip Isola
On the Learning and Learnability of Quasimetrics. ICLR (2022)
Wei-Cheng Tseng, Tsun-Hsuan Johnson Wang, Yen-Chen Lin, Phillip Isola
Offline Multi-Agent Reinforcement Learning with Knowledge Distillation. NeurIPS (2022)
Swami Sankaranarayanan, Anastasios N. Angelopoulos, Stephen Bates, Yaniv Romano, Phillip Isola
Semantic uncertainty intervals for disentangled latent spaces. CoRR (2022)
Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang
Any-Resolution Training for High-Resolution Image Synthesis. ECCV (16) (2022)
Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola
Generative Models as a Data Source for Multiview Representation Learning. ICLR (2022)
Miriam Cha, Kuan Wei Huang, Morgan Schmidt, Gregory Angelides, Mark Hamilton, Sam Goldberg, Armando Cabrera, Phillip Isola, Taylor Perron, Bill Freeman, Yen-Chen Lin, Brandon Swenson, Jean E. Piou
MultiEarth 2022 - Multimodal Learning for Earth and Environment Workshop and Challenge. CoRR (2022)
Manel Baradad, Chun-Fu Chen, Jonas Wulff, Tongzhou Wang, Rogério Feris, Antonio Torralba, Phillip Isola
Procedural Image Programs for Representation Learning. CoRR (2022)
Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez, Phillip Isola
NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields. ICRA (2022)
Yen-Chen Lin, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola
MIRA: Mental Imagery for Robotic Affordances. CoRR (2022)
Tongzhou Wang, Simon Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
Denoised MDPs: Learning World Models Better Than the World Itself. ICML (2022)
Vijay Gadepally, Gregory Angelides, Andrei Barbu, Andrew Bowne, Laura J. Brattain, Tamara Broderick, Armando Cabrera, Glenn Carl, Ronisha Carter, Miriam Cha, Emilie Cowen, Jesse Cummings, Bill Freeman, James R. Glass, Sam Goldberg, Mark Hamilton, Thomas Heldt, Kuan Wei Huang, Phillip Isola, Boris Katz, Jamie Koerner, Yen-Chen Lin, David Mayo, Kyle McAlpin, Taylor Perron, Jean E. Piou, Hrishikesh M. Rao, Hayley Reynolds, Kaira Samuel, Siddharth Samsi, Morgan Schmidt, Leslie Shing, Olga Simek, Brandon Swenson, Vivienne Sze, Jonathan Taylor, Paul Tylkin, Mark Veillette, Matthew L. Weiss, Allan B. Wollaber, Sophia Yuditskaya, Jeremy Kepner
Developing a Series of AI Challenges for the United States Department of the Air Force. CoRR (2022)
Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, Phillip Isola
Visual Prompting: Modifying Pixel Space to Adapt Pre-trained Models. CoRR (2022)
Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola
The Low-Rank Simplicity Bias in Deep Networks. CoRR (2021)
Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, Bingcheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade. NeurIPS (Competition and Demos) (2021)
Toru Lin, Jacob Huh, Christopher Stauffer, Ser-Nam Lim, Phillip Isola
Learning to Ground Multi-Agent Communication with Autoencoders. NeurIPS (2021)
Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba, Joshua B. Tenenbaum, Phillip Isola
OPEn: An Open-ended Physics Environment for Learning Without a Task. IROS (2021)
Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang
Contrastive Feature Loss for Image Prediction. ICCVW (2021)
Kenneth Derek, Phillip Isola
Adaptable Agent Populations via a Generative Model of Policies. CoRR (2021)
Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola
Generative Models as a Data Source for Multiview Representation Learning. CoRR (2021)
Yilun Du, Chuang Gan, Phillip Isola
Curious Representation Learning for Embodied Intelligence. ICCV (2021)
Yilun Du, Chuang Gan, Phillip Isola
Curious Representation Learning for Embodied Intelligence. CoRR (2021)
Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang
Ensembling With Deep Generative Views. CVPR (2021)
Lucy Chai, Jonas Wulff, Phillip Isola
Using latent space regression to analyze and leverage compositionality in GANs. CoRR (2021)
Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola
The Neural MMO Platform for Massively Multiagent Research. NeurIPS Datasets and Benchmarks (2021)
Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin
Learning to See before Learning to Act: Visual Pre-training for Manipulation. CoRR (2021)
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. CoRR (2021)
Toru Lin, Minyoung Huh, Chris Stauffer, Ser-Nam Lim, Phillip Isola
Learning to Ground Multi-Agent Communication with Autoencoders. CoRR (2021)
Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang
Ensembling with Deep Generative Views. CoRR (2021)
Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang
Contrastive Feature Loss for Image Prediction. CoRR (2021)
Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba
Learning to See by Looking at Noise. CoRR (2021)
Lucy Chai, Jonas Wulff, Phillip Isola
Using latent space regression to analyze and leverage compositionality in GANs. ICLR (2021)
Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri
Explaining in Style: Training a GAN to explain a classifier in StyleSpace. ICCV (2021)
Kenneth Derek, Phillip Isola
Adaptable Agent Populations via a Generative Model of Policies. NeurIPS (2021)
Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba, Joshua B. Tenenbaum, Phillip Isola
OPEn: An Open-ended Physics Environment for Learning Without a Task. CoRR (2021)
Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. IROS (2021)
Manel Baradad Jurjo, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba
Learning to See by Looking at Noise. NeurIPS (2021)
Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola
The Neural MMO Platform for Massively Multiagent Research. CoRR (2021)
Tongzhou Wang, Phillip Isola
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. ICML (2020)
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)
Ali Jahanian, Lucy Chai, Phillip Isola
On the "steerability" of generative adversarial networks. 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)
Yen-Chen Lin, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin
Learning to See before Learning to Act: Visual Pre-training for Manipulation. ICRA (2020)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What Makes for Good Views for Contrastive Learning? NeurIPS (2020)
Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. CoRR (2020)
Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum
Noisy Agents: Self-supervised Exploration by Predicting Auditory Events. CoRR (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)
Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola
What makes fake images detectable? Understanding properties that generalize. 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)
Yen-Chen Lin, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin
iNeRF: Inverting Neural Radiance Fields for Pose Estimation. CoRR (2020)
Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola
What Makes Fake Images Detectable? Understanding Properties that Generalize. ECCV (26) (2020)
Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. AAMAS (2020)
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola
What makes for good views for contrastive learning. CoRR (2020)
Tongzhou Wang, Phillip Isola
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Phillip Isola