Joshua M. Susskind

According to our database, Joshua M. Susskind authored at least 84 papers between 2008 and 2025.

Collaborative distances:

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

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

CoRR, July, 2025

TADA: Improved Diffusion Sampling with Training-free Augmented Dynamics.

Tianrong Chen, Huangjie Zheng, David Berthelot, Jiatao Gu, Josh M. Susskind, Shuangfei Zhai

CoRR, June, 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, Josh M. Susskind, Shuangfei Zhai

CoRR, June, 2025

How PARTs assemble into wholes: Learning the relative composition of images.

Melika Ayoughi, Samira Abnar, Chen Huang, Christopher Michael Sandino, Sayeri Lala, Eeshan Gunesh Dhekane, Dan Busbridge, Shuangfei Zhai, Vimal Thilak, Joshua M. Susskind, Pascal Mettes, Paul Groth, Hanlin Goh

CoRR, June, 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

CoRR, May, 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

CoRR, April, 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, April, 2025

Mechanisms of Projective Composition of Diffusion Models.

Arwen Bradley, Preetum Nakkiran, David Berthelot, James Thornton, Joshua M. Susskind

CoRR, February, 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, January, 2025

Improving GFlowNets for Text-to-Image Diffusion Alignment.

Dinghuai Zhang, Yizhe Zhang, Jiatao Gu, Ruixiang Zhang, Joshua M. Susskind, Navdeep Jaitly, Shuangfei Zhai

Trans. Mach. Learn. Res., 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

Proceedings of the Thirteenth International Conference on Learning Representations, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

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, Moin Nabi, Yinfei Yang, Joshua M. Susskind, Alaaeldin El-Nouby

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

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

3D Shape Tokenization.

Jen-Hao Rick Chang, Yuyang Wang, Miguel Ángel Bautista, Jiatao Gu, Joshua M. Susskind, Oncel Tuzel

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, Navdeep Jaitly, Joshua M. Susskind

CoRR, 2024

Coordinate In and Value Out: Training Flow Transformers in Ambient Space.

Yuyang Wang, Anurag Ranjan, Joshua M. Susskind, Miguel Ángel Bautista

CoRR, 2024

World-consistent Video Diffusion with Explicit 3D Modeling.

Qihang Zhang, Shuangfei Zhai, Miguel Ángel Bautista, Kevin Miao, Alexander Toshev, Joshua M. Susskind, Jiatao Gu

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

CoRR, 2024

DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation.

Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Josh M. Susskind, Shuangfei Zhai

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, Björn Ommer

CoRR, 2024

Many-to-many Image Generation with Auto-regressive Diffusion Models.

Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu

CoRR, 2024

How Far Are We from Intelligent Visual Deductive Reasoning?

Yizhe Zhang, He Bai, Ruixiang Zhang, Jiatao Gu, Shuangfei Zhai, Josh M. Susskind, Navdeep Jaitly

CoRR, 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, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling.

Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP.

Chen Huang, Skyler Seto, Samira Abnar, David Grangier, Navdeep Jaitly, Joshua M. Susskind

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Swallowing the Bitter Pill: Simplified Scalable Conformer Generation.

Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Data-free Distillation of Diffusion Models with Bootstrapping.

Jiatao Gu, Chen Wang, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Joshua M. Susskind

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization.

Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Matryoshka Diffusion Models.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Manifold Diffusion Fields.

Ahmed A. A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generative Modeling with Phase Stochastic Bridge.

Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai

Proceedings of the Twelfth International Conference on Learning Representations, 2024

When can transformers reason with abstract symbols?

Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pseudo-Generalized Dynamic View Synthesis from a Video.

Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Construction of Paired Knowledge Graph - Text Datasets Informed by Cyclic Evaluation.

Ali Mousavi, Xin Zhan, He Bai, Peng Shi, Theodoros Rekatsinas, Benjamin Han, Yunyao Li, Jeffrey Pound, Joshua M. Susskind, Natalie Schluter, Ihab F. Ilyas, Navdeep Jaitly

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Control3Diff: Learning Controllable 3D Diffusion Models from Single-view Images.

Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, Josh M. Susskind

Proceedings of the International Conference on 3D Vision, 2024

2023

Generating Molecular Conformer Fields.

Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista

CoRR, 2023

Adaptivity and Modularity for Efficient Generalization Over Task Complexity.

Samira Abnar, Omid Saremi, Laurent Dinh, Shantel Wilson, Miguel Ángel Bautista, Chen Huang, Vimal Thilak, Etai Littwin, Jiatao Gu, Josh M. Susskind, Samy Bengio

CoRR, 2023

Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today?

Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing

CoRR, 2023

Generative Modeling with Phase Stochastic Bridges.

Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Josh M. Susskind, Shuangfei Zhai

CoRR, 2023

Boolformer: Symbolic Regression of Logic Functions with Transformers.

Stéphane d'Ascoli, Samy Bengio, Josh M. Susskind, Emmanuel Abbe

CoRR, 2023

Value function estimation using conditional diffusion models for control.

Bogdan Mazoure, Walter Talbott, Miguel Ángel Bautista, R. Devon Hjelm, Alexander Toshev, Joshua M. Susskind

CoRR, 2023

BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Lingjie Liu, Josh M. Susskind

CoRR, 2023

Manifold Diffusion Fields.

Ahmed A. A. Elhag, Joshua M. Susskind, Miguel Ángel Bautista

CoRR, 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

Transformers learn through gradual rank increase.

Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind

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

PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model.

Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly

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

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the International Conference on Machine Learning, 2023

Diffusion Probabilistic Fields.

Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista

Proceedings of the Eleventh International Conference on Learning Representations, 2023

f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation.

Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind

Proceedings of the Eleventh International Conference on Learning Representations, 2023

MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors.

Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation.

Martin Bertran Lopez, Walter Talbott, Nitish Srivastava, Joshua M. Susskind

CoRR, 2022

Fast and Explicit Neural View Synthesis.

Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan

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

GAUDI: A Neural Architect for Immersive 3D Scene Generation.

Miguel Ángel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, Joshua M. Susskind

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

Regularized Training of Nearest Neighbor Language Models.

Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, 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

Proceedings of the International Conference on Machine Learning, 2022

Efficient Representation Learning via Adaptive Context Pooling.

Chen Huang, Walter Talbott, Navdeep Jaitly, Joshua M. Susskind

Proceedings of the International Conference on Machine Learning, 2022

Learning Representation from Neural Fisher Kernel with Low-rank Approximation.

Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind

Proceedings of the Tenth International Conference on Learning Representations, 2022

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

Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks.

Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua 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

An Attention Free Transformer.

Shuangfei Zhai, Walter Talbott, Nitish Srivastava, Chen Huang, Hanlin Goh, Ruixiang Zhang, Josh M. Susskind

CoRR, 2021

On the generalization of learning-based 3D reconstruction.

Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning.

Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

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

Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding.

Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Ángel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind

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

Unconstrained Scene Generation with Locally Conditioned Radiance Fields.

Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind

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

MetricOpt: Learning To Optimize Black-Box Evaluation Metrics.

Chen Huang, Shuangfei Zhai, Pengsheng Guo, Josh M. Susskind

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

2020

Set Distribution Networks: a Generative Model for Sets of Images.

Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Carlos Guestrin, Josh M. Susskind

CoRR, 2020

Equivariant Neural Rendering.

Emilien Dupont, Miguel Ángel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh M. Susskind, Qi Shan

CoRR, 2020

Collegial Ensembles.

Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan

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

Equivariant Neural Rendering.

Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh M. Susskind, Qi Shan

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

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

Adversarial Fisher Vectors for Unsupervised Representation Learning.

Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind

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

Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment.

Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind

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

2013

Modeling Natural Images Using Gated MRFs.

Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton

IEEE Trans. Pattern Anal. Mach. Intell., 2013

2011

Modeling the joint density of two images under a variety of transformations.

Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

On deep generative models with applications to recognition.

Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2008

Analysis-by-Synthesis by Learning to Invert Generative Black Boxes.

Vinod Nair, Joshua M. Susskind, Geoffrey E. Hinton

Proceedings of the Artificial Neural Networks, 2008