Analysis-by-Synthesis by Learning to Invert Generative Black Boxes. - Vinod Nair; Joshua M. Susskind; Geoffrey E. Hinton (ICANN (1), 2008)

On deep generative models with applications to recognition. - Marc'Aurelio Ranzato; Joshua M. Susskind; Volodymyr Mnih; Geoffrey E. Hinton (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)

Modeling Natural Images Using Gated MRFs. - Marc'Aurelio Ranzato; Volodymyr Mnih; Joshua M. Susskind; Geoffrey E. Hinton (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. - Chen Huang 001; Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Shih-Yu Sun; Carlos Guestrin; Joshua M. Susskind (ICML, 2019)

Adversarial Fisher Vectors for Unsupervised Representation Learning. - Shuangfei Zhai; Walter Talbott; Carlos Guestrin; Joshua M. Susskind (NeurIPS, 2019)

Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking. - Alaaeldin El-Nouby; Shuangfei Zhai; Graham W. Taylor; Joshua M. Susskind (CoRR, 2019)

Equivariant Neural Rendering. - Emilien Dupont; Miguel Bautista Martin; Alex Colburn; Aditya Sankar; Josh M. Susskind; Qi Shan (ICML, 2020)

Collegial Ensembles. - Etai Littwin; Ben Myara; Sima Sabah; Joshua M. Susskind; Shuangfei Zhai; Oren Golan (NeurIPS, 2020)

Equivariant Neural Rendering. - Emilien Dupont; Miguel Ángel Bautista 001; Alex Colburn; Aditya Sankar; Carlos Guestrin; Josh M. Susskind; Qi Shan (CoRR, 2020)

Set Distribution Networks: a Generative Model for Sets of Images. - Shuangfei Zhai; Walter Talbott; Miguel Ángel Bautista 001; Carlos Guestrin; Josh M. Susskind (CoRR, 2020)

MetricOpt: Learning To Optimize Black-Box Evaluation Metrics. - Chen Huang 001; Shuangfei Zhai; Pengsheng Guo; Josh M. Susskind (CVPR, 2021)

Unconstrained Scene Generation with Locally Conditioned Radiance Fields. - Terrance DeVries; Miguel Ángel Bautista 001; Nitish Srivastava; Graham W. Taylor; Joshua M. Susskind (ICCV, 2021)

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding. - Mike Roberts 001; Jason Ramapuram; Anurag Ranjan; Atulit Kumar; Miguel Ángel Bautista 001; Nathan Paczan; Russ Webb; Joshua M. Susskind (ICCV, 2021)

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. - Yue Wu 001; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind; Jian Zhang 050; Ruslan Salakhutdinov; Hanlin Goh (ICML, 2021)

On the generalization of learning-based 3D reconstruction. - Miguel Ángel Bautista 001; Walter Talbott; Shuangfei Zhai; Nitish Srivastava; Joshua M. Susskind (WACV, 2021)

An Attention Free Transformer. - Shuangfei Zhai; Walter Talbott; Nitish Srivastava; Chen Huang 001; Hanlin Goh; Ruixiang Zhang; Josh M. Susskind (CoRR, 2021)

Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. - Etai Littwin; Omid Saremi; Shuangfei Zhai; Vimal Thilak; Hanlin Goh; Joshua M. Susskind; Greg Yang (CoRR, 2021)

Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks. - Shih-Yu Sun; Vimal Thilak; Etai Littwin; Omid Saremi; Joshua M. Susskind (CoRR, 2021)

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models. - Nitish Srivastava; Walter Talbott; Martin Bertran Lopez; Shuangfei Zhai; Josh M. Susskind (CoRR, 2021)

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

Efficient Representation Learning via Adaptive Context Pooling. - Chen Huang 001; Walter Talbott; Navdeep Jaitly; 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 001; Hanlin Goh; Joshua M. Susskind (ICML, 2022)

Regularized Training of Nearest Neighbor Language Models. - Jean-Francois Ton; Walter Talbott; Shuangfei Zhai; Joshua M. Susskind (NAACL-HLT (Student Research Workshop), 2022)

GAUDI: A Neural Architect for Immersive 3D Scene Generation. - Miguel Ángel Bautista 001; Pengsheng Guo; Samira Abnar; Walter Talbott; Alexander Toshev; Zhuoyuan Chen; Laurent Dinh; Shuangfei Zhai; Hanlin Goh; Daniel Ulbricht; Afshin Dehghan; Joshua M. Susskind (NeurIPS, 2022)

Fast and Explicit Neural View Synthesis. - Pengsheng Guo; Miguel Ángel Bautista 001; Alex Colburn; Liang Yang; Daniel Ulbricht; Joshua M. Susskind; Qi Shan (WACV, 2022)

Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation. - Martin Bertran Lopez; Walter Talbott; Nitish Srivastava; Joshua M. Susskind (CoRR, 2022)

The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon. - Vimal Thilak; Etai Littwin; Shuangfei Zhai; Omid Saremi; Roni Paiss; Joshua M. Susskind (CoRR, 2022)

MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors. - Chen Huang 001; Hanlin Goh; Jiatao Gu; Joshua M. Susskind (ICLR, 2023)

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. - Jiatao Gu; Shuangfei Zhai; Yizhe Zhang 002; Miguel Ángel Bautista 001; Joshua M. Susskind (ICLR, 2023)

Diffusion Probabilistic Fields. - Peiye Zhuang; Samira Abnar; Jiatao Gu; Alexander G. Schwing; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICLR, 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 002; Jiatao Gu; Joshua M. Susskind (ICML, 2023)

PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. - Yizhe Zhang 002; Jiatao Gu; Zhuofeng Wu 001; Shuangfei Zhai; Joshua M. Susskind; Navdeep Jaitly (NeurIPS, 2023)

Transformers learn through gradual rank increase. - Emmanuel Abbe; Samy Bengio; Enric Boix-Adserà; Etai Littwin; Joshua M. Susskind (NeurIPS, 2023)

Learning Controllable 3D Diffusion Models from Single-view Images. - Jiatao Gu; Qingzhe Gao; Shuangfei Zhai; Baoquan Chen; Lingjie Liu; Josh M. Susskind (CoRR, 2023)

Manifold Diffusion Fields. - Ahmed A. A. Elhag; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2023)

BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping. - Jiatao Gu; Shuangfei Zhai; Yizhe Zhang 002; Lingjie Liu; Josh M. Susskind (CoRR, 2023)

Value function estimation using conditional diffusion models for control. - Bogdan Mazoure; Walter Talbott; Miguel Ángel Bautista 001; R. Devon Hjelm; Alexander Toshev; Joshua M. Susskind (CoRR, 2023)

Boolformer: Symbolic Regression of Logic Functions with Transformers. - Stéphane d'Ascoli; Samy Bengio; Josh M. Susskind; Emmanuel Abbe (CoRR, 2023)

Generative Modeling with Phase Stochastic Bridges. - Tianrong Chen; Jiatao Gu; Laurent Dinh; Evangelos A. Theodorou; Josh M. Susskind; Shuangfei Zhai (CoRR, 2023)

Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today? - Xiaoming Zhao 001; Alex Colburn; Fangchang Ma; Miguel Ángel Bautista 001; Joshua M. Susskind; Alexander G. Schwing (CoRR, 2023)

Adaptivity and Modularity for Efficient Generalization Over Task Complexity. - Samira Abnar; Omid Saremi; Laurent Dinh; Shantel Wilson; Miguel Ángel Bautista 001; Chen Huang 001; Vimal Thilak; Etai Littwin; Jiatao Gu; Josh M. Susskind; Samy Bengio (CoRR, 2023)

Generating Molecular Conformer Fields. - Yuyang Wang; Ahmed A. A. Elhag; Navdeep Jaitly; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2023)

Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images. - Jiatao Gu; Qingzhe Gao; Shuangfei Zhai; Baoquan Chen; Lingjie Liu; Josh M. Susskind (3DV, 2024)

Construction of Paired Knowledge Graph - Text Datasets Informed by Cyclic Evaluation. - Ali Mousavi 003; Xin Zhan; He Bai 002; Peng Shi 010; Theodoros Rekatsinas; Benjamin Han; Yunyao Li 001; Jeffrey Pound; Joshua M. Susskind; Natalie Schluter; Ihab F. Ilyas; Navdeep Jaitly (LREC/COLING, 2024)

Pseudo-Generalized Dynamic View Synthesis from a Video. - Xiaoming Zhao 001; Alex Colburn; Fangchang Ma; Miguel Ángel Bautista 001; Joshua M. Susskind; Alexander G. Schwing (ICLR, 2024)

When can transformers reason with abstract symbols? - Enric Boix-Adserà; Omid Saremi; Emmanuel Abbe; Samy Bengio; Etai Littwin; Joshua M. Susskind (ICLR, 2024)

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

Manifold Diffusion Fields. - Ahmed A. A. Elhag; Yuyang Wang; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICLR, 2024)

Matryoshka Diffusion Models. - Jiatao Gu; Shuangfei Zhai; Yizhe Zhang 002; Joshua M. Susskind; Navdeep Jaitly (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)

LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. - Vimal Thilak; Chen Huang 001; Omid Saremi; Laurent Dinh; Hanlin Goh; Preetum Nakkiran; Joshua M. Susskind; Etai Littwin (ICLR, 2024)

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. - Yuhang Zang; Hanlin Goh; Joshua M. Susskind; Chen Huang 001 (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)

Scalable Pre-training of Large Autoregressive Image Models. - Alaaeldin El-Nouby; Michal Klein; Shuangfei Zhai; Miguel Ángel Bautista 001; Vaishaal Shankar; Alexander T. Toshev; Joshua M. Susskind; Armand Joulin (ICML, 2024)

Data-free Distillation of Diffusion Models with Bootstrapping. - Jiatao Gu; Chen Wang 049; Shuangfei Zhai; Yizhe Zhang 002; Lingjie Liu; Joshua M. Susskind (ICML, 2024)

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation. - Yuyang Wang; Ahmed A. A. Elhag; Navdeep Jaitly; Joshua M. Susskind; Miguel Ángel Bautista 001 (ICML, 2024)

Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP. - Chen Huang 001; Skyler Seto; Samira Abnar; David Grangier; Navdeep Jaitly; Joshua M. Susskind (NeurIPS, 2024)

Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. - Jiatao Gu; Ying Shen 006; Shuangfei Zhai; Yizhe Zhang 002; Navdeep Jaitly; Joshua M. Susskind (NeurIPS, 2024)

How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. - Etai Littwin; Omid Saremi; Madhu Advani; Vimal Thilak; Preetum Nakkiran; Chen Huang 001; Joshua M. Susskind (NeurIPS, 2024)

How Far Are We from Intelligent Visual Deductive Reasoning? - Yizhe Zhang 002; He Bai 002; Ruixiang Zhang; Jiatao Gu; Shuangfei Zhai; Josh M. Susskind; Navdeep Jaitly (CoRR, 2024)

Many-to-many Image Generation with Auto-regressive Diffusion Models. - Ying Shen 006; Yizhe Zhang 002; Shuangfei Zhai; Lifu Huang; Joshua M. Susskind; Jiatao Gu (CoRR, 2024)

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. - Nick Stracke; Stefan Andreas Baumann; Joshua M. Susskind; Miguel Ángel Bautista 001; Björn Ommer (CoRR, 2024)

DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation. - Jiatao Gu; Yuyang Wang; Yizhe Zhang 002; Qihang Zhang; Dinghuai Zhang; Navdeep Jaitly; Josh M. Susskind; Shuangfei Zhai (CoRR, 2024)

TypeScore: A Text Fidelity Metric for Text-to-Image Generative Models. - Georgia Gabriela Sampaio; Ruixiang Zhang; Shuangfei Zhai; Jiatao Gu; Josh M. Susskind; Navdeep Jaitly; Yizhe Zhang 002 (CoRR, 2024)

World-consistent Video Diffusion with Explicit 3D Modeling. - Qihang Zhang; Shuangfei Zhai; Miguel Ángel Bautista 001; Kevin Miao; Alexander Toshev; Joshua M. Susskind; Jiatao Gu (CoRR, 2024)

Coordinate In and Value Out: Training Flow Transformers in Ambient Space. - Yuyang Wang; Anurag Ranjan; Joshua M. Susskind; Miguel Ángel Bautista 001 (CoRR, 2024)

Normalizing Flows are Capable Generative Models. - Shuangfei Zhai; Ruixiang Zhang; Preetum Nakkiran; David Berthelot; Jiatao Gu; Huangjie Zheng; Tianrong Chen; Miguel Ángel Bautista 001; Navdeep Jaitly; Joshua M. Susskind (CoRR, 2024)

3D Shape Tokenization. - Jen-Hao Rick Chang; Yuyang Wang; Miguel Ángel Bautista 001; Jiatao Gu; Joshua M. Susskind; Oncel Tuzel (CoRR, 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 (Trans. Mach. Learn. Res., 2024)

Multimodal Autoregressive Pre-training of Large Vision Encoders. - Enrico Fini; Mustafa Shukor; Xiujun Li; Philipp Dufter; Michal Klein; David Haldimann; Sai Aitharaju; Victor G. Turrisi da Costa; Louis Béthune; Zhe Gan; Alexander Toshev; Marcin Eichner; et al. (CVPR, 2025)

World-consistent Video Diffusion with Explicit 3D Modeling. - Qihang Zhang; Shuangfei Zhai; Miguel Ángel Bautista Martin; Kevin Miao; Alexander Toshev; Joshua M. Susskind; Jiatao Gu (CVPR, 2025)

Denoising Autoregressive Transformers for Scalable Text-to-Image Generation. - Jiatao Gu; Yuyang Wang; Yizhe Zhang 002; Qihang Zhang; Dinghuai Zhang; Navdeep Jaitly; Joshua M. Susskind; Shuangfei Zhai (ICLR, 2025)

Improving GFlowNets for Text-to-Image Diffusion Alignment. - Dinghuai Zhang; Yizhe Zhang 002; Jiatao Gu; Ruixiang Zhang; Joshua M. Susskind; Navdeep Jaitly; Shuangfei Zhai (Trans. Mach. Learn. Res., 2025)

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models. - Samira Abnar; Harshay Shah; Dan Busbridge; Alaaeldin Mohamed Elnouby Ali; Joshua M. Susskind; Vimal Thilak (CoRR, 2025)

Mechanisms of Projective Composition of Diffusion Models. - Arwen Bradley; Preetum Nakkiran; David Berthelot; James Thornton; Joshua M. Susskind (CoRR, 2025)

Scaling Laws for Native Multimodal Models. - Mustafa Shukor; Enrico Fini; Victor Guilherme Turrisi da Costa; Matthieu Cord; Joshua M. Susskind; Alaaeldin El-Nouby (CoRR, 2025)

Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion. - Ruixiang Zhang; Shuangfei Zhai; Yizhe Zhang 002; James Thornton; Zijing Ou; Joshua M. Susskind; Navdeep Jaitly (CoRR, 2025)

Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting. - Chen Huang 001; Skyler Seto; Hadi Pouransari; Mehrdad Farajtabar; Raviteja Vemulapalli; Fartash Faghri; Oncel Tuzel; Barry-John Theobald; Joshua M. Susskind (CoRR, 2025)

How PARTs assemble into wholes: Learning the relative composition of images. - Melika Ayoughi; Samira Abnar; Chen Huang 001; Christopher Michael Sandino; Sayeri Lala; Eeshan Gunesh Dhekane; Dan Busbridge; Shuangfei Zhai; Vimal Thilak; Joshua M. Susskind; Pascal Mettes; Paul Groth; et al. (CoRR, 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 001; Josh M. Susskind; Shuangfei Zhai (CoRR, 2025)

TADA: Improved Diffusion Sampling with Training-free Augmented Dynamics. - Tianrong Chen; Huangjie Zheng; David Berthelot; Jiatao Gu; Josh M. Susskind; Shuangfei Zhai (CoRR, 2025)

Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows. - Ruixiang Zhang; Shuangfei Zhai; Jiatao Gu; Yizhe Zhang 002; Huangjie Zheng; Tianrong Chen; Miguel Ángel Bautista 001; Joshua M. Susskind; Navdeep Jaitly (CoRR, 2025)