Aaron Lou - RankMe

25 papers A* 12Journal 13

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Denoising Diffusion Bridge Models. ICLR Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
2024	A*	`conf`	Diffusion Model Alignment Using Direct Preference Optimization. CVPR Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
2024	A*	`conf`	Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution. ICML Aaron Lou, Chenlin Meng, Stefano Ermon
2024	A*	`conf`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. ICML Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	J	`jnl`	Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
2024	A*	`conf`	Geometric Trajectory Diffusion Models. NeurIPS Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon
2024	J	`jnl`	Geometric Trajectory Diffusion Models. CoRR Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon
2023	J	`jnl`	Denoising Diffusion Bridge Models. CoRR Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
2023	J	`jnl`	Diffusion Model Alignment Using Direct Preference Optimization. CoRR Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
2023	J	`jnl`	Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution. CoRR Aaron Lou, Chenlin Meng, Stefano Ermon
2023	A*	`conf`	Reflected Diffusion Models. ICML Aaron Lou, Stefano Ermon
2023	J	`jnl`	Reflected Diffusion Models. CoRR Aaron Lou, Stefano Ermon
2023	A*	`conf`	Riemannian Residual Neural Networks. NeurIPS Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa
2023	J	`jnl`	Riemannian Residual Neural Networks. CoRR Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa
2023	A*	`conf`	Scaling Riemannian Diffusion Models. NeurIPS Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon
2023	J	`jnl`	Scaling Riemannian Diffusion Models. CoRR Aaron Lou, Minkai Xu, Stefano Ermon
2021	A*	`conf`	Equivariant Manifold Flows. NeurIPS Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021	J	`jnl`	Equivariant Manifold Flows. CoRR Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2021	A*	`conf`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. NeurIPS Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2021	J	`jnl`	Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. CoRR Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
2020	A*	`conf`	Differentiating through the Fréchet Mean. ICML Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
2020	J	`jnl`	Differentiating through the Fréchet Mean. CoRR Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
2020	A*	`conf`	Neural Manifold Ordinary Differential Equations. NeurIPS Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2020	J	`jnl`	Neural Manifold Ordinary Differential Equations. CoRR Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
2018	J	`jnl`	Adversarial Example Decomposition. CoRR Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Pian Pawakapan, Serge J. Belongie, Ser-Nam Lim