Susskind, Joshua M.

50 publications

ICLR 2025 Denoising Autoregressive Transformers for Scalable Text-to-Image Generation Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Joshua M. Susskind, Shuangfei Zhai

NeurIPS 2025 Flexible Language Modeling in Continuous Space with Transformer-Based Autoregressive Flows Ruixiang Zhang, Shuangfei Zhai, Jiatao Gu, Yizhe Zhang, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Joshua M. Susskind, Navdeep Jaitly

ICML 2025 INRFlow: Flow Matching for INRs in Ambient Space Yuyang Wang, Anurag Ranjan, Joshua M. Susskind, Miguel Ángel Bautista

TMLR 2025 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICML 2025 Mechanisms of Projective Composition of Diffusion Models Arwen Bradley, Preetum Nakkiran, David Berthelot, James Thornton, Joshua M. Susskind

ICML 2025 Normalizing Flows Are Capable Generative Models Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel Ángel Bautista, Navdeep Jaitly, Joshua M. Susskind

ICML 2025 Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models Samira Abnar, Harshay Shah, Dan Busbridge, Alaaeldin El-Nouby, Joshua M. Susskind, Vimal Thilak

ICLRW 2025 Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models Samira Abnar, Harshay Shah, Dan Busbridge, Alaaeldin El-Nouby, Joshua M. Susskind, Vimal Thilak

ICML 2025 Proxy-FDA: Proxy-Based Feature Distribution Alignment for Fine-Tuning Vision Foundation Models Without Forgetting Chen Huang, Skyler Seto, Hadi Pouransari, Mehrdad Farajtabar, Raviteja Vemulapalli, Fartash Faghri, Oncel Tuzel, Barry-John Theobald, Joshua M. Susskind

NeurIPS 2025 STARFlow: Scaling Latent Normalizing Flows for High-Resolution Image Synthesis Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Ángel Bautista, Joshua M. Susskind, Shuangfei Zhai

NeurIPS 2025 TADA: Improved Diffusion Sampling with Training-Free Augmented DynAmics Tianrong Chen, Huangjie Zheng, David Berthelot, Jiatao Gu, Joshua M. Susskind, Shuangfei Zhai

ICML 2025 Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion Ruixiang Zhang, Shuangfei Zhai, Yizhe Zhang, James Thornton, Zijing Ou, Joshua M. Susskind, Navdeep Jaitly

ICML 2024 Data-Free Distillation of Diffusion Models with Bootstrapping Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind

ICLR 2024 Generative Modeling with Phase Stochastic Bridge Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos Theodorou, Joshua M. Susskind, Shuangfei Zhai

ICLRW 2024 How Far Are We from Intelligent Visual Deductive Reasoning? Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly

ICMLW 2024 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICMLW 2024 Improving GFlowNets for Text-to-Image Diffusion Alignment Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

ICMLW 2024 Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind

ICLR 2024 LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin

ICLR 2024 Manifold Diffusion Fields Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista

ICMLW 2024 Many-to-Many Image Generation with Auto-Regressive Diffusion Models Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu

ICLR 2024 Matryoshka Diffusion Models Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly

NeurIPSW 2024 On the Ricci Curvature of Attention Maps and Transformers Training and Robustness Amirhossein Farzam, Oded Schlesinger, Joshua M. Susskind, Juan Matias Di Martino, Guillermo Sapiro

ICLR 2024 Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang

ICLR 2024 Pseudo-Generalized Dynamic View Synthesis from a Video Xiaoming Zhao, R Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alex Schwing

ICML 2024 Scalable Pre-Training of Large Autoregressive Image Models Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Vaishaal Shankar, Alexander T Toshev, Joshua M. Susskind, Armand Joulin

ICML 2024 Swallowing the Bitter Pill: Simplified Scalable Conformer Generation Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

ICMLW 2024 Swallowing the Bitter Pill: Simplified Scalable Conformer Generation Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

TMLR 2024 The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind

ICLR 2024 Vanishing Gradients in Reinforcement Finetuning of Language Models Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin

ICLR 2024 What Algorithms Can Transformers Learn? a Study in Length Generalization Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran

ICLR 2024 When Can Transformers Reason with Abstract Symbols? Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind

ICMLW 2023 BOOT: Data-Free Distillation of Denoising Diffusion Models with Bootstrapping Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind

ICLR 2023 Diffusion Probabilistic Fields Peiye Zhuang, Samira Abnar, Jiatao Gu, Alex Schwing, Joshua M. Susskind, Miguel Ángel Bautista

ICLR 2023 F-DM: A Multi-Stage Diffusion Model via Progressive Signal Transformation Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind

ICLR 2023 MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind

ICML 2023 NerfDiff: Single-Image View Synthesis with NeRF-Guided Distillation from 3D-Aware Diffusion Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M. Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi

ICML 2023 Stabilizing Transformer Training by Preventing Attention Entropy Collapse Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind

ICML 2022 Efficient Representation Learning via Adaptive Context Pooling Chen Huang, Walter Talbott, Navdeep Jaitly, Joshua M Susskind

WACV 2022 Fast and Explicit Neural View Synthesis Pengsheng Guo, Miguel Angel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan

ICLR 2022 Learning Representation from Neural Fisher Kernel with Low-Rank Approximation Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind

ICML 2022 Position Prediction as an Effective Pretraining Strategy Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M Susskind

NeurIPSW 2022 The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the \emph{Grokking Phenomenon} Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind

ICCV 2021 Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Angel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind

WACV 2021 On the Generalization of Learning-Based 3D Reconstruction Miguel Angel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind

NeurIPSW 2021 Robust Robotic Control from Pixels Using Contrastive Recurrent State-Space Models Nitish Srivastava, Walter Talbott, Martin Bertran Lopez, Shuangfei Zhai, Joshua M. Susskind

ICML 2021 Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

ICCV 2021 Unconstrained Scene Generation with Locally Conditioned Radiance Fields Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

CVPR 2011 Modeling the Joint Density of Two Images Under a Variety of Transformations Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys

CVPR 2011 On Deep Generative Models with Applications to Recognition Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton