Jain, Ayush

29 publications

NeurIPS 2025 Actor-Free Continuous Control via Structurally Maximizable Q-Functions Yigit Korkmaz, Urvi Bhuwania, Ayush Jain, Erdem Biyik

ICML 2025 From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs Ang Cao, Sergio Arnaud, Oleksandr Maksymets, Jianing Yang, Ayush Jain, Ada Martin, Vincent-Pierre Berges, Paul Mcvay, Ruslan Partsey, Aravind Rajeswaran, Franziska Meier, Justin Johnson, Jeong Joon Park, Alexander Sax

NeurIPS 2025 Grounded Reinforcement Learning for Visual Reasoning Gabriel Herbert Sarch, Snigdha Saha, Naitik Khandelwal, Ayush Jain, Michael J. Tarr, Aviral Kumar, Katerina Fragkiadaki

ICML 2025 LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D Paul Mcvay, Sergio Arnaud, Ada Martin, Arjun Majumdar, Krishna Murthy Jatavallabhula, Phillip Thomas, Ruslan Partsey, Daniel Dugas, Abha Gejji, Alexander Sax, Vincent-Pierre Berges, Mikael Henaff, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

ICLR 2025 QMP: Q-Switch Mixture of Policies for Multi-Task Behavior Sharing Grace Zhang, Ayush Jain, Injune Hwang, Shao-Hua Sun, Joseph J Lim

ICML 2025 Unifying 2D and 3D Vision-Language Understanding Ayush Jain, Alexander Swerdlow, Yuzhou Wang, Sergio Arnaud, Ada Martin, Alexander Sax, Franziska Meier, Katerina Fragkiadaki

NeurIPSW 2024 A Physics Enforced Neural Network to Predict Polymer Melt Viscosity Ayush Jain, Rishi Gurnani, Arunkumar Rajan, Hang Jerry Qi, Rampi Ramprasad

CVPR 2024 Diffusion-ES: Gradient-Free Planning with Diffusion for Autonomous and Instruction-Guided Driving Brian Yang, Huangyuan Su, Nikolaos Gkanatsios, Tsung-Wei Ke, Ayush Jain, Jeff Schneider, Katerina Fragkiadaki

NeurIPS 2024 Linear Regression Using Heterogeneous Data Batches Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky

CVPR 2024 ODIN: A Single Model for 2D and 3D Segmentation Ayush Jain, Pushkal Katara, Nikolaos Gkanatsios, Adam W. Harley, Gabriel Sarch, Kriti Aggarwal, Vishrav Chaudhary, Katerina Fragkiadaki

NeurIPS 2024 Scaling Laws for Learning with Real and Surrogate Data Ayush Jain, Andrea Montanari, Eren Sasoglu

ICML 2023 Efficient List-Decodable Regression Using Batches Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen

ECCV 2022 Bottom up Top Down Detection Transformers for Language Grounding in Images and Point Clouds Ayush Jain, Nikolaos Gkanatsios, Ishita Mediratta, Katerina Fragkiadaki

NeurIPSW 2022 Efficient Multi-Task Reinforcement Learning via Selective Behavior Sharing Grace Zhang, Ayush Jain, Injune Hwang, Shao-Hua Sun, Joseph J Lim

ICLR 2022 Know Your Action Set: Learning Action Relations for Reinforcement Learning Ayush Jain, Norio Kosaka, Kyung-Min Kim, Joseph J Lim

COLT 2022 Robust Estimation for Random Graphs Jayadev Acharya, Ayush Jain, Gautam Kamath, Ananda Theertha Suresh, Huanyu Zhang

ICML 2022 Scalable Deep Reinforcement Learning Algorithms for Mean Field Games Mathieu Lauriere, Sarah Perrin, Sertan Girgin, Paul Muller, Ayush Jain, Theophile Cabannes, Georgios Piliouras, Julien Perolat, Romuald Elie, Olivier Pietquin, Matthieu Geist

ICML 2022 TURF: Two-Factor, Universal, Robust, Fast Distribution Learning Algorithm Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar

COLT 2022 The Price of Tolerance in Distribution Testing Clement L Canonne, Ayush Jain, Gautam Kamath, Jerry Li

ICML 2021 Robust Density Estimation from Batches: The Best Things in Life Are (Nearly) Free Ayush Jain, Alon Orlitsky

UAI 2021 Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan

AAAI 2021 Variance Penalized On-Policy and Off-Policy Actor-Critic Arushi Jain, Gandharv Patil, Ayush Jain, Khimya Khetarpal, Doina Precup

NeurIPS 2020 A General Method for Robust Learning from Batches Ayush Jain, Alon Orlitsky

ICML 2020 Generalization to New Actions in Reinforcement Learning Ayush Jain, Andrew Szot, Joseph Lim

NeurIPS 2020 Linear-Sample Learning of Low-Rank Distributions Ayush Jain, Alon Orlitsky

ICML 2020 Optimal Robust Learning of Discrete Distributions from Batches Ayush Jain, Alon Orlitsky

NeurIPS 2020 SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm Yi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar

ECCVW 2020 VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results Dawei Du, Longyin Wen, Pengfei Zhu, Heng Fan, Qinghua Hu, Haibin Ling, Mubarak Shah, Junwen Pan, Apostolos Axenopoulos, Arne Schumann, Athanasios Psaltis, Ayush Jain, Bin Dong, Changlin Li, Chen Chen, Chengzhen Duan, Chongyang Zhang, Daniel Stadler, Dheeraj Reddy Pailla, Dong Yin, Faizan Khan, Fanman Meng, Guangyu Gao, Guosheng Zhang, Hansheng Chen, Hao Zhou, Haonian Xie, Heqian Qiu, Hongliang Li, Ioannis Athanasiadis, Jincai Cui, Jingkai Zhou, Jong Hwan Ko, Joo Chan Lee, Jun Yu, Jungyeop Yoo, Lars Wilko Sommer, Lu Xiong, Michael Schleiss, Ming-Hsuan Yang, Mingyu Liu, Minjian Zhang, Murari Mandal, Petros Daras, Pratik Narang, Qiong Liu, Qiu Shi, Qizhang Lin, Rohit Ramaprasad, Sai Wang, Sarvesh Mehta, Shuai Li, Shuqin Huang, Sungtae Moon, Taijin Zhao, Ting Sun, Wei Guo, Wei Tian, Weida Qin, Weiping Yu, Wenxiang Lin, Xi Zhao, Xiaogang Jia, Xin He, Xingjie Zhao, Xuanxin Liu, Yan Ding, Yan Luo, Yang Xiao, Yi Wang, Yingjie Liu, Yongwoo Kim, Yu Sun, Yuehan Yao, Yuyao Huang, Zehui Gong, Zhenyu Xu, Zhipeng Luo, Zhiguo Cao, Zhiwei Wei, Zhongjie Fan, Zichen Song, Ziming Liu

ICML 2018 The Limits of Maxing, Ranking, and Preference Learning Moein Falahatgar, Ayush Jain, Alon Orlitsky, Venkatadheeraj Pichapati, Vaishakh Ravindrakumar