Phillip Isola

Papers

This list may be incomplete. For a complete and up to date list of publications please see Google Scholar.

2024
	Scalable Optimization in the Modular Norm Tim Large, Yang Liu, Minyoung Huh, Hyojin Bahng, Phillip Isola, Jeremy Bernstein NeurIPS 2024. [Paper][Code][Docs][Slides]
	The Platonic Representation Hypothesis Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola ICML 2024 (Position Paper, Oral). [Paper][Website][Code]
	Training Neural Networks from Scratch with Parallel Low-Rank Adapters Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola, Pulkit Agrawal arXiv 2024. [Paper][Website][Code]
	LangNav: Language as a Perceptual Representation for Navigation Bowen Pan, Rameswar Panda, SouYoung Jin, Rogerio Feris, Aude Oliva, Phillip Isola, Yoon Kim NAACL 2024 (Findings). [Paper][Code][Model]
	Learning Vision from Models Rivals Learning Vision from Data Yonglong Tian, Lijie Fan, Kaifeng Chen, Dina Katabi, Dilip Krishnan, Phillip Isola CVPR 2024. [Paper][Code]
	Scaling Laws of Synthetic Images for Model Training ... for Now Lijie Fan, Kaifeng Chen, Dilip Krishnan, Dina Katabi, Phillip Isola, Yonglong Tian CVPR 2024. [Paper][Code]
	A Vision Check-up for Language Models Pratyusha Sharma, Tamar Rott Shaham, Manel Baradad, Stephanie Fu, Adrian Rodriguez-Munoz, Shivam Duggal, Phillip Isola, Antonio Torralba CVPR 2024 (highlight). [Paper][Website]
2023
	Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning 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 NeurIPS 2023 Track on Datasets and Benchmarks. [Paper][Website][Code][Competitions]
	Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation William Shen, Ge Yang, Alan Yu, Jansen Wong, Leslie Kaelbling, Phillip Isola CoRL 2023 (best paper award). [Paper][Website][Code][Video]
	Learning New Dimensions of Human Visual Similarity using Synthetic Data Stephanie Fu, Netanel Tamir, Shobhita Sundaram, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola NeurIPS 2023 (spotlight)*. [Paper][Website][Code/Data][Colab]
	StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan NeurIPS 2023. [Paper]
	Improving CLIP Training with Language Rewrites Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian NeurIPS 2023. [Paper][Code]
	Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola ICML 2023. [Paper][Website][Code]
	Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang ICML 2023. [Paper][Website][Code]
	Persistent Nature: A Generative Model of Unbounded 3D Worlds Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely CVPR 2023. [Paper][Website][Code]
	Powderworld: A Platform for Understanding Generalization via Rich Task Distributions Kevin Frans, Phillip Isola ICLR 2023 (notable top 25%). [Paper][Blog + Demo][Code]
	The Low-Rank Simplicity Bias in Deep Networks Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola TMLR 2023. [Paper][Website][Code]
2022
	Improved Representation of Asymmetrical Distances with Interval Quasimetric Embeddings Tongzhou Wang, Phillip Isola NeurReps Workshop 2022. [Paper][Website][Code]
	MIRA: Mental Imagery for Robotic Affordances Lin Yen-Chen, Pete Florence, Andy Zeng, Jonathan T. Barron, Yilun Du, Wei-Chiu Ma, Anthony Simeonov, Alberto Rodriguez Garcia, Phillip Isola CoRL 2022. [Paper][Website][Video]
	Semantic uncertainty intervals for disentangled latent spaces Swami Sankaranarayanan, Anastasios Angelopoulos, Stephen Bates, Yaniv Romoano, Phillip Isola NeurIPS 2022. [Paper][Website][Code][Video]
	Procedural Image Programs for Representation Learning Manel Baradad, Chun-Fu (Richard) Chen, Jonas Wulff, Tongzhou Wang, Rogerio Feris, Antonio Torralba, Phillip Isola NeurIPS 2022. [Paper][Website][Code & Datasets]
	Offline Multi-Agent Reinforcement Learning with Knowledge Distillation Wei-Cheng Tseng, Tsun-Hsuan Wang, Lin Yen-Chen, Phillip Isola NeurIPS 2022. [Paper]
	Totems: Physical Objects for Verifying Visual Integrity Jingwei Ma, Lucy Chai, Minyoung Huh, Tongzhou Wang, Sernam Lim, Phillip Isola, Antonio Torralba ECCV 2022. [Paper][Website][Code][Video]
	Any-resolution Training for High-resolution Image Synthesis Lucy Chai, Michaël Gharbi, Eli Shechtman, Phillip Isola, Richard Zhang ECCV 2022. [Paper][Website][Code][Video]
	Denoised MDPs: Learning World Models Better Than The World Itself Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian ICML 2022. [Paper][Website][Code]
	Exploring Visual Prompts for Adapting Large-Scale Models Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, Phillip Isola arXiv 2022. [Paper][Website][Code]
	Learning to generate line drawings that convey geometry and semantics Caroline Chan, Frédo Durand, Phillip Isola CVPR 2022. [Paper][Website][Code][Demo]
	On the Learning and Learnability of Quasimetrics Tongzhou Wang, Phillip Isola ICLR 2022. [Paper][Website][Code]
	Generative Models as a Data Source for Multiview Representation Learning Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola ICLR 2022. [Paper][Website][Code][News article]
	NeRF-Supervision: Learning Dense Object Descriptors from Neural Radiance Fields Lin Yen-Chen, Pete Florence, Jonathan T. Barron, Tsung-Yi Lin, Alberto Rodriguez, Phillip Isola ICRA 2022. [Paper][Website][Video][Code][Colab]
	Noisy Agents: Self-supervised Exploration by Predicting Auditory Events Chuang Gan, Xiaoyu Chen, Phillip Isola, Antonio Torralba, Joshua B. Tenenbaum IROS 2022. [Paper][Website]
2021
	Learning to Ground Multi-Agent Communication with Autoencoders Toru Lin, Jacob Huh, Chris Stauffer, Sernam Lim, Phillip Isola NeurIPS 2021. [Paper][Website][Code]
	The Neural MMO Platform for Massively Multiagent Research Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola NeurIPS 2021, Track on Datasets and Benchmarks. [Pre-print][Website][Code][Competition]
	Adaptable Agent Populations Using a Generative Model of Policies Kenneth Derek, Phillip Isola NeurIPS 2021. [Paper][Website][Code]
	Learning to See by Looking at Noise Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba NeurIPS 2021 (spotlight). [Paper][Website][Code]
	Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman, Michal Yarom, Yoav Wald, Gal Elidan, Avinatan Hassidim, William T. Freeman, Phillip Isola, Amir Globerson, Michal Irani, Inbar Mosseri ICCV 2021. [Paper][Website][Code]
	Curious Representation Learning for Embodied Intelligence Yilun Du, Chuang Gan, Phillip Isola ICCV 2021. [Paper][Website][Code]
	iNeRF: Inverting Neural Radiance Fields for Pose Estimation Lin Yen-Chen, Pete Florence, Jonathan T. Barron, Alberto Rodriguez, Phillip Isola, Tsung-Yi Lin IROS 2021. [Paper][Website]
	OPEn: An Open-ended Physics Environment for Learning Without a Task Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba, Joshua B.Tenenbaum, Phillip Isola IROS 2021. [Paper][Website]
	Ensembling with Deep Generative Views Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhang CVPR 2021. [Paper][Website][Code][Colab]
	Using latent space regression to analyze and leverage compositionality in GANs Lucy Chai, Jonas Wulff, Phillip Isola ICLR 2021. [Paper][Website][Code][Demo (Colab)]
2020
	What makes for good views for contrastive learning? Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola NeurIPS 2020. [Paper][Website][Code][Blog]
	Supervised Contrastive Learning Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan NeurIPS 2020. [Paper][Code]
	What makes fake images detectable? Understanding properties that generalize Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola ECCV 2020. [Paper][Website][Code]
	Rethinking Few-Shot Image Classification: A Good Embedding Is All You Need? Yonglong Tian, Yue Wang, Dilip Krishnan, Josh Tenenbaum, Phillip Isola ECCV 2020. [Paper][Website][Code]
	Contrastive Multiview Coding Yonglong Tian, Dilip Krishnan, Phillip Isola ECCV 2020. [Paper][Website][Code]
	Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere Tongzhou Wang, Phillip Isola ICML 2020. [Paper][Website][Code]
	Learning to See before Learning to Act: Visual Pre-training for Manipulation Lin Yen-Chen, Andy Zeng, Shuran Song, Phillip Isola, Tsung-Yi Lin ICRA 2020. [Paper][Website][Code][Video][Blog]
	Contrastive Representation Distillation Yonglong Tian, Dilip Krishnan, Phillip Isola ICLR 2020. [Paper][Website][Code]
	On the "steerability" of generative adversarial networks Ali Jahanian, Lucy Chai, Phillip Isola ICLR 2020. [Paper][Website][Code]
2019
	Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch arXiv 2019. [Paper][Blog][Code]
	Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity Deepak Pathak, Chris Lu, Trevor Darrell, Phillip Isola, Alexei A. Efros NeurIPS 2019 (spotlight). Winner of Virtual Creatures Competition at GECCO 2019 (link) [Paper][Website][Code]
	GANalyze: Toward Visual Definitions of Cognitive Image Properties Lore Goetschalckx, Alex Andonian, Aude Oliva, Phillip Isola ICCV 2019. [Paper][Website][Code]
	InGAN: Capturing and Remapping the "DNA" of a Natural Image Assaf Shocher, Shai Bagon, Phillip Isola, Michal Irani ICCV 2019 (oral). [Paper][Website][Code]
	Experience-embedded Visual Foresight Lin Yen-Chen, Maria Bauza, Phillip Isola CoRL 2019. [Paper][Website][Code]
	Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGBD images Maria Bauza, Ferran Alet, Yen-Chen Lin, Tomas Lozano-Perez, Leslie P. Kaelbling, Phillip Isola, Alberto Rodriguez IROS 2019. [Paper][Website]
2018
	Evolved Policy Gradients Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel NeurIPS 2018 (spotlight). [Paper][Blog][Code]
	CyCADA: Cycle-Consistent Adversarial Domain Adaptation Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell ICML 2018. [Paper]
	Memorable words are monogamous: The role of synonymy and homonymy in word recognition memory Kyle Mahowald, Phillip Isola, Evelina Fedorenko, Edward Gibson, Aude Oliva PsyArXiv 2018. [Paper]
	The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, Oliver Wang CVPR 2018. [Paper][Website][Code]
	What You Sketch Is What You Get: 3D Sketching using Multi-View Deep Volumetric Prediction Johanna Delanoy, Adrien Bousseau, Mathieu Aubry, Phillip Isola, Alexei A. Efros I3D 2018. [Paper][Video]
2017
	Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks Jun-Yan Zhu, Taesung Park, Phillip Isola, Alexei A. Efros ICCV 2017 (spotlight). [Paper][Website][Code]
	Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation Ashvin Nair, Pulkit Agrawal, Dian Chen, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine ICRA 2017. [Paper][Website][Video]
	Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S. Lin, Tianhe Yu, Alexei A. Efros Real-Time User-Guided Image Colorization with Learned Deep Priors SIGGRAPH 2017. [Paper][Website][Code][Video]
	Ali Jahanian, Phillip Isola, Donglai Wei Mining Visual Evolution in 21 Years of Web Design CHI Extended Abstract, 2017. [Paper]
	Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros Image-to-Image Translation with Conditional Adversarial Networks CVPR, 2017. [Paper][Website][Code][Demo]
	Richard Zhang, Phillip Isola, Alexei A. Efros Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction CVPR, 2017. [Paper][Website][Code]
2016
	Richard Zhang, Phillip Isola, Alexei A. Efros Colorful Image Colorization European Conference on Computer Vision (ECCV), 2016 (oral). [Paper][Website][Code][Demo]
	Andrew Owens, Phillip Isola, Josh McDermott, Antonio Torralba, Edward H. Adelson, William T. Freeman Visually Indicated Sounds IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 (oral). [Paper][Website][Video][Dataset (50GB)]
	Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson Learning Visual Groups From Co-occurrences in Space and Time International Conference on Learning Representations, Workshop paper, 2016 [Paper]
2015
	Daniel Zoran, Phillip Isola, Dilip Krishnan, William T. Freeman Learning Ordinal Relationships for Mid-Level Vision International Conference on Computer Vision (ICCV), 2015. [Paper][Website][Code]
	Phillip Isola, Joseph J. Lim, Edward H. Adelson Discovering States and Transformations in Image Collections IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015 (oral). [Paper][Website][Dataset]
	Zoya Bylinskii, Phillip Isola, Constance Bainbridge, Antonio Torralba, Aude Oliva Intrinsic and Extrinsic Effects on Image Memorability Vision Research, 2015. [Paper][Website][Code][Dataset]
	Zhengdong Zhang, Phillip Isola, Edward H. Adelson Sparkle Vision: Seeing the World through Random Specular Microfacets 4th IEEE International Workshop on Computational Cameras and Displays, 2015. [Paper]
2014
	Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson Crisp Boundary Detection Using Pointwise Mutual Information European Conference on Computer Vision (ECCV), 2014 (oral). [Paper][Website][Code]
2013
	Phillip Isola, Jianxiong Xiao, Devi Parikh, Antonio Torralba, Aude Oliva What Makes a Photograph Memorable? Pattern Analysis and Machine Intelligence (PAMI), 2013. [Paper][Website][Dataset]
	Phillip Isola and Ce Liu Scene Collaging: Analysis and Synthesis of Natural Images with Semantic Layers. International Conference on Computer Vision (ICCV), 2013. [Paper][Website]
	Michelle Borkin, Azalea Vo, Zoya Bylinskii, Phillip Isola, Shashank Sunkavalli, Aude Oliva, Hanspeter Pfister What Makes a Visualization Memorable? IEEE Transactions on Visualization and Computer Graphics (Infovis), 2013. [Paper][Website]
	Wilma A. Bainbridge, Phillip Isola, Aude Oliva The Intrinsic Memorability of Face Images. Journal of Experimental Psychology: General, 2013. [Paper][Website][Dataset]
	Aude Oliva, Phillip Isola, Aditya Khosla, Wilma A. Bainbridge What makes a picture memorable? SPIE Newsroom Article, 2013. [Article]
2012
	Aditya Khosla, Jianxiong Xiao, Phillip Isola, Antonio Torralba, Aude Oliva Image Memorability and Visual Inception. SIGGRAPH Asia Technical Briefs (Invited Paper), 2012. [Paper]
	Forrester Cole, Phillip Isola, William T. Freeman, Fredo Durand, Edward H. Adelson Shapecollage: Occlusion-aware, example-based shape interpretation. European Conference on Computer Vision (ECCV), 2012. [Paper][Website]
	Wilma A. Bainbridge, Phillip Isola, Idan Blank, Aude Oliva Establishing a database for studying human face photograph memorability. Proceedings of the Annual Conference of the Cognitive Sciences Society, 2012. [Paper][Website][Dataset]
2011
	Phillip Isola, Devi Parikh, Antonio Torralba, Aude Oliva Understanding the intrinsic memorability of images. NeurIPS, 2011. [Paper]Website]
	Phillip Isola, Jianxiong Xiao, Antonio Torralba, Aude Oliva What makes an image memorable? IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [Paper][Website][Dataset]
2008
	Nicholas B. Turk-Browne, Phillip Isola, Brian J. Scholl, Teresa A. Treat Multidimensional visual statistical learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 2008. [Paper]