Joshua M. Susskind

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 59

Top Topics

Diffusion Models

Top Venues

Publications

Ahmed A. Elhag, Yuyang Wang, Joshua M. Susskind, Miguel Ángel Bautista
Manifold Diffusion Fields. ICLR (2024)
Yuhang Zang, Hanlin Goh, Joshua M. Susskind, Chen Huang
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization. ICLR (2024)
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M. Susskind, Navdeep Jaitly
Matryoshka Diffusion Models. ICLR (2024)
Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing
Pseudo-Generalized Dynamic View Synthesis from a Video. ICLR (2024)
Tianrong Chen, Jiatao Gu, Laurent Dinh, Evangelos A. Theodorou, Joshua M. Susskind, Shuangfei Zhai
Generative Modeling with Phase Stochastic Bridge. ICLR (2024)
Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu
Many-to-many Image Generation with Auto-regressive Diffusion Models. CoRR (2024)
Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
Vanishing Gradients in Reinforcement Finetuning of Language Models. ICLR (2024)
Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. ICLR (2024)
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
Construction of Paired Knowledge Graph - Text Datasets Informed by Cyclic Evaluation. LREC/COLING (2024)
Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Joshua M. Susskind, Samy Bengio, Preetum Nakkiran
What Algorithms can Transformers Learn? A Study in Length Generalization. ICLR (2024)
Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind
When can transformers reason with abstract symbols? ICLR (2024)
Nick Stracke, Stefan Andreas Baumann, Joshua M. Susskind, Miguel Ángel Bautista, Björn Ommer
CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. CoRR (2024)
Alaaeldin El-Nouby, Michal Klein, Shuangfei Zhai, Miguel Ángel Bautista, Alexander Toshev, Vaishaal Shankar, Joshua M. Susskind, Armand Joulin
Scalable Pre-training of Large Autoregressive Image Models. CoRR (2024)
Jiatao Gu, Ying Shen, Shuangfei Zhai, Yizhe Zhang, Navdeep Jaitly, Joshua M. Susskind
Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling. CoRR (2024)
Etai Littwin, Omid Saremi, Madhu Advani, Vimal Thilak, Preetum Nakkiran, Chen Huang, Joshua M. Susskind
How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks. CoRR (2024)
Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind
The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods. Trans. Mach. Learn. Res. 2024 (2024)
Chen Huang, Hanlin Goh, Jiatao Gu, Joshua M. Susskind
MAST: Masked Augmentation Subspace Training for Generalizable Self-Supervised Priors. ICLR (2023)
Yizhe Zhang, Jiatao Gu, Zhuofeng Wu, Shuangfei Zhai, Joshua M. Susskind, Navdeep Jaitly
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. NeurIPS (2023)
Yuyang Wang, Ahmed A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel Ángel Bautista
Generating Molecular Conformer Fields. CoRR (2023)
Ahmed A. Elhag, Joshua M. Susskind, Miguel Ángel Bautista
Manifold Diffusion Fields. CoRR (2023)
Noam Razin, Hattie Zhou, Omid Saremi, Vimal Thilak, Arwen Bradley, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
Vanishing Gradients in Reinforcement Finetuning of Language Models. CoRR (2023)
Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M. Susskind, Christian Theobalt, Lingjie Liu, Ravi Ramamoorthi
NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusion. ICML (2023)
Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe, Samy Bengio, Etai Littwin, Joshua M. Susskind
When can transformers reason with abstract symbols? CoRR (2023)
Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista
Diffusion Probabilistic Fields. ICLR (2023)
Bogdan Mazoure, Walter Talbott, Miguel Ángel Bautista, R. Devon Hjelm, Alexander Toshev, Joshua M. Susskind
Value function estimation using conditional diffusion models for control. CoRR (2023)
Vimal Thilak, Chen Huang, Omid Saremi, Laurent Dinh, Hanlin Goh, Preetum Nakkiran, Joshua M. Susskind, Etai Littwin
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures. CoRR (2023)
Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. CoRR (2023)
Enric Boix-Adserà, Etai Littwin, Emmanuel Abbe, Samy Bengio, Joshua M. Susskind
Transformers learn through gradual rank increase. CoRR (2023)
Peiye Zhuang, Samira Abnar, Jiatao Gu, Alexander G. Schwing, Joshua M. Susskind, Miguel Ángel Bautista
Diffusion Probabilistic Fields. CoRR (2023)
Emmanuel Abbe, Samy Bengio, Enric Boix-Adserà, Etai Littwin, Joshua M. Susskind
Transformers learn through gradual rank increase. NeurIPS (2023)
Xiaoming Zhao, Alex Colburn, Fangchang Ma, Miguel Ángel Bautista, Joshua M. Susskind, Alexander G. Schwing
Is Generalized Dynamic Novel View Synthesis from Monocular Videos Possible Today? CoRR (2023)
Shuangfei Zhai, Tatiana Likhomanenko, Etai Littwin, Dan Busbridge, Jason Ramapuram, Yizhe Zhang, Jiatao Gu, Joshua M. Susskind
Stabilizing Transformer Training by Preventing Attention Entropy Collapse. ICML (2023)
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, Joshua M. Susskind
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation. ICLR (2023)
Chen Huang, Walter Talbott, Navdeep Jaitly, Joshua M. Susskind
Efficient Representation Learning via Adaptive Context Pooling. ICML (2022)
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
GAUDI: A Neural Architect for Immersive 3D Scene Generation. NeurIPS (2022)
Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind
The Slingshot Mechanism: An Empirical Study of Adaptive Optimizers and the Grokking Phenomenon. CoRR (2022)
Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan
Fast and Explicit Neural View Synthesis. WACV (2022)
Martin Bertran Lopez, Walter Talbott, Nitish Srivastava, Joshua M. Susskind
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation. CoRR (2022)
Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Y. Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind
Position Prediction as an Effective Pretraining Strategy. ICML (2022)
Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua M. Susskind
Learning Representation from Neural Fisher Kernel with Low-rank Approximation. ICLR (2022)
Jean-Francois Ton, Walter Talbott, Shuangfei Zhai, Joshua M. Susskind
Regularized Training of Nearest Neighbor Language Models. NAACL-HLT (Student Research Workshop) (2022)
Shuangfei Zhai, Navdeep Jaitly, Jason Ramapuram, Dan Busbridge, Tatiana Likhomanenko, Joseph Yitan Cheng, Walter Talbott, Chen Huang, Hanlin Goh, Joshua M. Susskind
Position Prediction as an Effective Pretraining Strategy. CoRR (2022)
Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind
On the generalization of learning-based 3D reconstruction. WACV (2021)
Etai Littwin, Omid Saremi, Shuangfei Zhai, Vimal Thilak, Hanlin Goh, Joshua M. Susskind, Greg Yang
Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks. CoRR (2021)
Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. ICCV (2021)
Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua M. Susskind
Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks. CoRR (2021)
Pengsheng Guo, Miguel Ángel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, Qi Shan
Fast and Explicit Neural View Synthesis. CoRR (2021)
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. CoRR (2021)
Terrance DeVries, Miguel Ángel Bautista, Nitish Srivastava, Graham W. Taylor, Joshua M. Susskind
Unconstrained Scene Generation with Locally Conditioned Radiance Fields. CoRR (2021)
Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning. ICML (2021)
Mike Roberts, Jason Ramapuram, Anurag Ranjan, Atulit Kumar, Miguel Ángel Bautista, Nathan Paczan, Russ Webb, Joshua M. Susskind
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding. ICCV (2021)
Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan
Collegial Ensembles. NeurIPS (2020)
Etai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan
Collegial Ensembles. CoRR (2020)
Miguel Ángel Bautista, Walter Talbott, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind
On the generalization of learning-based 3D reconstruction. CoRR (2020)
Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind
Adversarial Fisher Vectors for Unsupervised Representation Learning. NeurIPS (2019)
Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. ICML (2019)
Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. CoRR (2019)
Alaaeldin El-Nouby, Shuangfei Zhai, Graham W. Taylor, Joshua M. Susskind
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking. CoRR (2019)
Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind
Adversarial Fisher Vectors for Unsupervised Representation Learning. CoRR (2019)
Marc'Aurelio Ranzato, Volodymyr Mnih, Joshua M. Susskind, Geoffrey E. Hinton
Modeling Natural Images Using Gated MRFs. IEEE Trans. Pattern Anal. Mach. Intell. 35 (9) (2013)
Marc'Aurelio Ranzato, Joshua M. Susskind, Volodymyr Mnih, Geoffrey E. Hinton
On deep generative models with applications to recognition. CVPR (2011)
Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys
Modeling the joint density of two images under a variety of transformations. CVPR (2011)
Vinod Nair, Joshua M. Susskind, Geoffrey E. Hinton
Analysis-by-Synthesis by Learning to Invert Generative Black Boxes. ICANN (1) (2008)