Aditya Grover - RankMe

165 papers A* 47A 9B 1Journal 98Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Enabling Autoregressive Models to Fill In Masked Tokens. EACL (Findings) Daniel Israel, Aditya Grover, Guy Van den Broeck
2026	J	`jnl`	LaViDa-R1: Advancing Reasoning for Unified Multimodal Diffusion Language Models. CoRR Shufan Li, Yuchen Zhu, Jiuxiang Gu, Kangning Liu, Zhe Lin, Yongxin Chen, Molei Tao, Aditya Grover, Jason Kuen
2026	J	`jnl`	SNCE: Geometry-Aware Supervision for Scalable Discrete Image Generation. CoRR Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Aditya Grover, Jason Kuen
2026	J	`jnl`	Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models. CoRR Siyan Zhao, Zhihui Xie, Mengchen Liu, Jing Huang, Guan Pang, Feiyu Chen, Aditya Grover
2025	J	`jnl`	Accelerating Diffusion LLMs via Adaptive Parallel Decoding. CoRR Daniel Israel, Guy Van den Broeck, Aditya Grover
2025	J	`jnl`	Accelerating Inference of Masked Image Generators via Reinforcement Learning. CoRR Pranav Subbaraman, Shufan Li, Siyan Zhao, Aditya Grover
2025	—	`conf`	Comparing Bad Apples to Good Oranges Aligning Large Language Models via Joint Preference Optimization. ACL (Findings) Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
2025	J	`jnl`	Enabling Autoregressive Models to Fill In Masked Tokens. CoRR Daniel Israel, Aditya Grover, Guy Van den Broeck
2025	J	`jnl`	From Masks to Worlds: A Hitchhiker's Guide to World Models. CoRR Jinbin Bai, Yu Lei, Hecong Wu, Yuchen Zhu, Shufan Li, Yi Xin, Xiangtai Li, Molei Tao, Aditya Grover, Ming-Hsuan Yang
2025	J	`jnl`	HoneyBee: Data Recipes for Vision-Language Reasoners. CoRR Hritik Bansal, Devandra Singh Sachan, Kai-Wei Chang, Aditya Grover, Gargi Ghosh, Wen-tau Yih, Ramakanth Pasunuru
2025	J	`jnl`	Iceberg: Enhancing HLS Modeling with Synthetic Data. CoRR Zijian Ding, Tung Nguyen, Weikai Li, Aditya Grover, Yizhou Sun, Jason Cong
2025	J	`jnl`	IndiaWeatherBench: A Dataset and Benchmark for Data-Driven Regional Weather Forecasting over India. CoRR Tung Nguyen, Harkanwar Singh, Nilay Naharas, Lucas Bandarkar, Aditya Grover
2025	J	`jnl`	Inpainting-Guided Policy Optimization for Diffusion Large Language Models. CoRR Siyan Zhao, Mengchen Liu, Jing Huang, Miao Liu, Chenyu Wang, Bo Liu, Yuandong Tian, Guan Pang, Sean Bell, Aditya Grover, Feiyu Chen
2025	—	`conf`	InstructAny2Pix: Image Editing with Multi-Modal Prompts. NAACL (Findings) Shufan Li, Harkanwar Singh, Aditya Grover
2025	A*	`conf`	LICO: Large Language Models for In-Context Molecular Optimization. ICLR Tung Nguyen, Aditya Grover
2025	J	`jnl`	LaViDa: A Large Diffusion Language Model for Multimodal Understanding. CoRR Shufan Li, Konstantinos Kallidromitis, Hritik Bansal, Akash Gokul, Yusuke Kato, Kazuki Kozuka, Jason Kuen, Zhe Lin, Kai-Wei Chang, Aditya Grover
2025	J	`jnl`	Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation. CoRR Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Zijun Wei, Aditya Grover, Jason Kuen
2025	J	`jnl`	Mercury: Ultra-Fast Language Models Based on Diffusion. CoRR Samar Khanna, Siddhant Kharbanda, Shufan Li, Harshit Varma, Eric Wang, Sawyer Birnbaum, Ziyang Luo, Yanis Miraoui, Akash Palrecha, Stefano Ermon, Aditya Grover, Volodymyr Kuleshov
2025	J	`jnl`	MobileWorldBench: Towards Semantic World Modeling For Mobile Agents. CoRR Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato, Kazuki Kozuka, Aditya Grover
2025	J	`jnl`	Multi-fidelity Reinforcement Learning Control for Complex Dynamical Systems. CoRR Luning Sun, Xin-Yang Liu, Siyan Zhao, Aditya Grover, Jian-Xun Wang, Jayaraman J. Thiagarajan
2025	J	`jnl`	OmniCast: A Masked Latent Diffusion Model for Weather Forecasting Across Time Scales. CoRR Tung Nguyen, Tuan Pham, Troy Arcomano, Veerabhadra Kotamarthi, Ian T. Foster, Sandeep Madireddy, Aditya Grover
2025	A*	`conf`	OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows. CVPR Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Zichun Liao, Yusuke Kato, Kazuki Kozuka, Aditya Grover
2025	J	`jnl`	OpenThoughts: Data Recipes for Reasoning Models. CoRR Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt
2025	J	`jnl`	PhysiX: A Foundation Model for Physics Simulations. CoRR Tung Nguyen, Arsh Koneru, Shufan Li, Aditya Grover
2025	J	`jnl`	Planned Diffusion. CoRR Daniel Israel, Tian Jin, Ellie Y. Cheng, Guy Van den Broeck, Aditya Grover, Suvinay Subramanian, Michael Carbin
2025	J	`jnl`	PredGen: Accelerated Inference of Large Language Models through Input-Time Speculation for Real-Time Speech Interaction. CoRR Shufan Li, Aditya Grover
2025	A	`conf`	Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models. AISTATS Siyan Zhao, Daniel Israel, Guy Van den Broeck, Aditya Grover
2025	J	`jnl`	Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection. CoRR Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Arsh Koneru, Yusuke Kato, Kazuki Kozuka, Aditya Grover
2025	J	`jnl`	Sparse-LaViDa: Sparse Multimodal Discrete Diffusion Language Models. CoRR Shufan Li, Jiuxiang Gu, Kangning Liu, Zhe Lin, Zijun Wei, Aditya Grover, Jason Kuen
2025	J	`jnl`	The Pitfalls of KV Cache Compression. CoRR Alex Chen, Renato Lui Geh, Aditya Grover, Guy Van den Broeck, Daniel Israel
2025	J	`jnl`	VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation. CoRR Hritik Bansal, Clark Peng, Yonatan Bitton, Roman Goldenberg, Aditya Grover, Kai-Wei Chang
2025	A*	`conf`	VideoPhy: Evaluating Physical Commonsense for Video Generation. ICLR Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
2025	J	`jnl`	WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusion. CoRR Vinay Shukla, Prachee Sharma, Ryan A. Rossi, Sungchul Kim, Tong Yu, Aditya Grover
2025	J	`jnl`	When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning. CoRR Nishad Singhi, Hritik Bansal, Arian Hosseini, Aditya Grover, Kai-Wei Chang, Marcus Rohrbach, Anna Rohrbach
2025	J	`jnl`	d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning. CoRR Siyan Zhao, Devaansh Gupta, Qinqing Zheng, Aditya Grover
2024	A*	`conf`	ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. NeurIPS Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine
2024	J	`jnl`	ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. CoRR Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine
2024	J	`jnl`	Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization. CoRR Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
2024	A*	`conf`	Group Preference Optimization: Few-Shot Alignment of Large Language Models. ICLR Siyan Zhao, John Dang, Aditya Grover
2024	J	`jnl`	LICO: Large Language Models for In-Context Molecular Optimization. CoRR Tung Nguyen, Aditya Grover
2024	J	`jnl`	Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data. CoRR Shufan Li, Harkanwar Singh, Aditya Grover
2024	—	`conf`	Mamba-ND: Selective State Space Modeling for Multi-dimensional Data. ECCV (33) Shufan Li, Harkanwar Singh, Aditya Grover
2024	J	`jnl`	MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants. CoRR Hritik Bansal, Daniel Israel, Siyan Zhao, Shufan Li, Tung Nguyen, Aditya Grover
2024	J	`jnl`	OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows. CoRR Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Zichun Liao, Yusuke Kato, Kazuki Kozuka, Aditya Grover
2024	J	`jnl`	Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback. CoRR Qinqing Zheng, Mikael Henaff, Amy Zhang, Aditya Grover, Brandon Amos
2024	A*	`conf`	Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models. ICLR Hritik Bansal, John Dang, Aditya Grover
2024	J	`jnl`	PopAlign: Population-Level Alignment for Fair Text-to-Image Generation. CoRR Shufan Li, Harkanwar Singh, Aditya Grover
2024	J	`jnl`	Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models. CoRR Siyan Zhao, Daniel Israel, Guy Van den Broeck, Aditya Grover
2024	A*	`conf`	Probing the Decision Boundaries of In-context Learning in Large Language Models. NeurIPS Siyan Zhao, Tung Nguyen, Aditya Grover
2024	J	`jnl`	Probing the Decision Boundaries of In-context Learning in Large Language Models. CoRR Siyan Zhao, Tung Nguyen, Aditya Grover
2024	J	`jnl`	Scaling Vision-and-Language Navigation With Offline RL. CoRR Valay Bundele, Mahesh Bhupati, Biplab Banerjee, Aditya Grover
2024	J	`jnl`	Scaling Vision-and-Language Navigation With Offline RL. Trans. Mach. Learn. Res. Valay Bundele, Mahesh Bhupati, Biplab Banerjee, Aditya Grover
2024	A*	`conf`	Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. NeurIPS Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Rao Kotamarthi, Ian T. Foster, Sandeep Madireddy, Aditya Grover
2024	J	`jnl`	TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation. CoRR Hritik Bansal, Yonatan Bitton, Michal Yarom, Idan Szpektor, Aditya Grover, Kai-Wei Chang
2024	A*	`conf`	VideoCon: Robust Video-Language Alignment via Contrast Captions. CVPR Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
2024	J	`jnl`	VideoPhy: Evaluating Physical Commonsense for Video Generation. CoRR Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
2023	A*	`conf`	CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. ICCV Hritik Bansal, Fan Yin, Nishad Singhi, Aditya Grover, Yu Yang, Kai-Wei Chang
2023	J	`jnl`	CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. CoRR Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang
2023	A*	`conf`	ClimaX: A foundation model for weather and climate. ICML Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
2023	J	`jnl`	ClimaX: A foundation model for weather and climate. CoRR Tung Nguyen, Johannes Brandstetter, Ashish Kapoor, Jayesh K. Gupta, Aditya Grover
2023	A*	`conf`	ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. NeurIPS Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
2023	J	`jnl`	ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. CoRR Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
2023	A*	`conf`	Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models. NeurIPS Siyan Zhao, Aditya Grover
2023	J	`jnl`	Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models. CoRR Siyan Zhao, Aditya Grover
2023	A*	`conf`	Diffusion Models for Black-Box Optimization. ICML Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover
2023	J	`jnl`	Diffusion Models for Black-Box Optimization. CoRR Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover
2023	A*	`conf`	ExPT: Synthetic Pretraining for Few-Shot Experimental Design. NeurIPS Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
2023	J	`jnl`	ExPT: Synthetic Pretraining for Few-Shot Experimental Design. CoRR Tung Nguyen, Sudhanshu Agrawal, Aditya Grover
2023	A*	`conf`	Generative Decision Making Under Uncertainty. AAAI Aditya Grover
2023	A*	`conf`	Generative Pretraining for Black-Box Optimization. ICML Satvik Mehul Mashkaria, Siddarth Krishnamoorthy, Aditya Grover
2023	J	`jnl`	Group Preference Optimization: Few-Shot Alignment of Large Language Models. CoRR Siyan Zhao, John Dang, Aditya Grover
2023	J	`jnl`	Guided Flows for Generative Modeling and Decision Making. CoRR Qinqing Zheng, Matt Le, Neta Shaul, Yaron Lipman, Aditya Grover, Ricky T. Q. Chen
2023	J	`jnl`	High Dimensional Causal Inference with Variational Backdoor Adjustment. CoRR Daniel Israel, Aditya Grover, Guy Van den Broeck
2023	J	`jnl`	InstructAny2Pix: Flexible Visual Editing via Multimodal Instruction Following. CoRR Shufan Li, Harkanwar Singh, Aditya Grover
2023	J	`jnl`	Leaving Reality to Imagination: Robust Classification via Generated Datasets. CoRR Hritik Bansal, Aditya Grover
2023	J	`jnl`	Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models. CoRR Hritik Bansal, John Dang, Aditya Grover
2023	J	`jnl`	Scaling Pareto-Efficient Decision Making Via Offline Multi-Objective RL. CoRR Baiting Zhu, Meihua Dang, Aditya Grover
2023	A*	`conf`	Scaling Pareto-Efficient Decision Making via Offline Multi-Objective RL. ICLR Baiting Zhu, Meihua Dang, Aditya Grover
2023	J	`jnl`	Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. CoRR Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover
2023	A*	`conf`	Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. ICML Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover
2023	J	`jnl`	VideoCon: Robust Video-Language Alignment via Contrast Captions. CoRR Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
2022	J	`jnl`	BARACK: Partially Supervised Group Robustness With Guarantees. CoRR Nimit Sharad Sohoni, Maziar Sanjabi, Nicolas Ballas, Aditya Grover, Shaoliang Nie, Hamed Firooz, Christopher Ré
2022	J	`jnl`	ConserWeightive Behavioral Cloning for Reliable Offline Reinforcement Learning. CoRR Tung Nguyen, Qinqing Zheng, Aditya Grover
2022	J	`jnl`	Controllable Generative Modeling via Causal Reasoning. Trans. Mach. Learn. Res. Joey Bose, Ricardo Pio Monti, Aditya Grover
2022	A*	`conf`	CyCLIP: Cyclic Contrastive Language-Image Pretraining. NeurIPS Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover
2022	J	`jnl`	CyCLIP: Cyclic Contrastive Language-Image Pretraining. CoRR Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover
2022	A*	`conf`	Frame Averaging for Invariant and Equivariant Network Design. ICLR Omri Puny, Matan Atzmon, Edward J. Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, Yaron Lipman
2022	A*	`conf`	Frozen Pretrained Transformers as Universal Computation Engines. AAAI Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
2022	J	`jnl`	Generative Pretraining for Black-Box Optimization. CoRR Siddarth Krishnamoorthy, Satvik Mehul Mashkaria, Aditya Grover
2022	J	`jnl`	Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning. CoRR Carl Qi, Pieter Abbeel, Aditya Grover
2022	A*	`conf`	It Takes Four to Tango: Multiagent Self Play for Automatic Curriculum Generation. ICLR Yuqing Du, Pieter Abbeel, Aditya Grover
2022	J	`jnl`	It Takes Four to Tango: Multiagent Selfplay for Automatic Curriculum Generation. CoRR Yuqing Du, Pieter Abbeel, Aditya Grover
2022	A	`conf`	Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. AISTATS Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady
2022	A*	`conf`	Masked Autoencoding for Scalable and Generalizable Decision Making. NeurIPS Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel
2022	J	`jnl`	Masked Autoencoding for Scalable and Generalizable Decision Making. CoRR Fangchen Liu, Hao Liu, Aditya Grover, Pieter Abbeel
2022	A*	`conf`	Matching Normalizing Flows and Probability Paths on Manifolds. ICML Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Maximilian Nickel, Aditya Grover, Ricky T. Q. Chen, Yaron Lipman
2022	J	`jnl`	Matching Normalizing Flows and Probability Paths on Manifolds. CoRR Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky T. Q. Chen, Yaron Lipman
2022	A*	`conf`	Online Decision Transformer. ICML Qinqing Zheng, Amy Zhang, Aditya Grover
2022	J	`jnl`	Online Decision Transformer. CoRR Qinqing Zheng, Amy Zhang, Aditya Grover
2022	J	`jnl`	Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories. CoRR Qinqing Zheng, Mikael Henaff, Brandon Amos, Aditya Grover
2022	A*	`conf`	Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling. ICML Tung Nguyen, Aditya Grover
2022	J	`jnl`	Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling. CoRR Tung Nguyen, Aditya Grover
2021	A*	`conf`	Anytime Sampling for Autoregressive Models via Ordered Autoencoding. ICLR Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
2021	J	`jnl`	Anytime Sampling for Autoregressive Models via Ordered Autoencoding. CoRR Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
2021	A*	`conf`	BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery. NeurIPS Chris Cundy, Aditya Grover, Stefano Ermon
2021	J	`jnl`	BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery. CoRR Chris Cundy, Aditya Grover, Stefano Ermon
2021	A*	`conf`	Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	J	`jnl`	Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	J	`jnl`	Frame Averaging for Invariant and Equivariant Network Design. CoRR Omri Puny, Matan Atzmon, Heli Ben-Hamu, Edward J. Smith, Ishan Misra, Aditya Grover, Yaron Lipman
2021	J	`jnl`	JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data. CoRR Kourosh Hakhamaneshi, Pieter Abbeel, Vladimir Stojanovic, Aditya Grover
2021	J	`jnl`	Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. CoRR Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya Muthukumar, Ashwin Pananjady
2021	A*	`conf`	Moser Flow: Divergence-based Generative Modeling on Manifolds. NeurIPS Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
2021	J	`jnl`	Moser Flow: Divergence-based Generative Modeling on Manifolds. CoRR Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
2021	A*	`conf`	PiRank: Scalable Learning To Rank via Differentiable Sorting. NeurIPS Robin M. E. Swezey, Aditya Grover, Bruno Charron, Stefano Ermon
2021	J	`jnl`	Pretrained Transformers as Universal Computation Engines. CoRR Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
2021	A*	`conf`	Reset-Free Lifelong Learning with Skill-Space Planning. ICLR Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
2021	J	`jnl`	Rotation Invariant Graph Neural Networks using Spin Convolutions. CoRR Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das, Aditya Grover, Anuroop Sriram, Zachary W. Ulissi, C. Lawrence Zitnick
2021	—	`conf`	The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev
2020	A*	`conf`	AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows. AAAI Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon
2020	J	`jnl`	Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nat. Peter M. Attia, Aditya Grover, Norman Jin, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz, Stefano Ermon, William C. Chueh
2020	A*	`conf`	Fair Generative Modeling via Weak Supervision. ICML Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon
2020	—	`—`	Learning to represent and reason under limited supervision. Aditya Grover
2020	A	`conf`	Permutation Invariant Graph Generation via Score-Based Generative Modeling. AISTATS Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon
2020	J	`jnl`	Permutation Invariant Graph Generation via Score-Based Generative Modeling. CoRR Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon
2020	J	`jnl`	PiRank: Learning To Rank via Differentiable Sorting. CoRR Robin M. E. Swezey, Aditya Grover, Bruno Charron, Stefano Ermon
2020	J	`jnl`	Reset-Free Lifelong Learning with Skill-Space Planning. CoRR Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch
2019	J	`jnl`	AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows. CoRR Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon
2019	—	`conf`	AlignFlow: Learning from multiple domains via normalizing flows. DGS@ICLR Aditya Grover, Christopher Chute, Rui Shu, Zhangjie Cao, Stefano Ermon
2019	A*	`conf`	Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting. NeurIPS Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon
2019	J	`jnl`	Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting. CoRR Aditya Grover, Jiaming Song, Alekh Agarwal, Kenneth Tran, Ashish Kapoor, Eric Horvitz, Stefano Ermon
2019	—	`conf`	Bias Correction of Learned Generative Models via Likelihood-free Importance Weighting. DGS@ICLR Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon
2019	J	`jnl`	Fair Generative Modeling via Weak Supervision. CoRR Aditya Grover, Kristy Choi, Rui Shu, Stefano Ermon
2019	A*	`conf`	Graphite: Iterative Generative Modeling of Graphs. ICML Aditya Grover, Aaron Zweig, Stefano Ermon
2019	A	`conf`	Learning Controllable Fair Representations. AISTATS Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon
2019	A*	`conf`	Neural Joint Source-Channel Coding. ICML Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, Stefano Ermon
2019	—	`conf`	Stochastic Optimization of Sorting Networks via Continuous Relaxations. ICLR (Poster) Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon
2019	J	`jnl`	Stochastic Optimization of Sorting Networks via Continuous Relaxations. CoRR Aditya Grover, Eric Wang, Aaron Zweig, Stefano Ermon
2019	A	`conf`	Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization. AISTATS Aditya Grover, Stefano Ermon
2018	A	`conf`	Best arm identification in multi-armed bandits with delayed feedback. AISTATS Aditya Grover, Todor M. Markov, Peter M. Attia, Norman Jin, Nicolas Perkins, Bryan Cheong, Michael H. Chen, Zi Yang, Stephen J. Harris, William C. Chueh, Stefano Ermon
2018	J	`jnl`	Best arm identification in multi-armed bandits with delayed feedback. CoRR Aditya Grover, Todor M. Markov, Peter M. Attia, Norman Jin, Nicholas Perkins, Bryan Cheong, Michael H. Chen, Zi Yang, Stephen J. Harris, William C. Chueh, Stefano Ermon
2018	A*	`conf`	Boosted Generative Models. AAAI Aditya Grover, Stefano Ermon
2018	A	`conf`	Evaluating Generalization in Multiagent Systems using Agent-Interaction Graphs. AAMAS Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards
2018	A*	`conf`	Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models. AAAI Aditya Grover, Manik Dhar, Stefano Ermon
2018	J	`jnl`	Graphite: Iterative Generative Modeling of Graphs. CoRR Aditya Grover, Aaron Zweig, Stefano Ermon
2018	J	`jnl`	Learning Controllable Fair Representations. CoRR Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon
2018	A*	`conf`	Learning Policy Representations in Multiagent Systems. ICML Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yuri Burda, Harrison Edwards
2018	J	`jnl`	Learning Policy Representations in Multiagent Systems. CoRR Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards
2018	A*	`conf`	Modeling Sparse Deviations for Compressed Sensing using Generative Models. ICML Manik Dhar, Aditya Grover, Stefano Ermon
2018	J	`jnl`	Modeling Sparse Deviations for Compressed Sensing using Generative Models. CoRR Manik Dhar, Aditya Grover, Stefano Ermon
2018	B	`conf`	ROGER: An On-Line Flight Efficiency Monitoring System Using ADS-B Data. MDM Shen Wang, Aditya Grover, Brian Mac Namee, Philip Plantholt, Javier Lopez-Leones, Pablo Sanchez-Escalonilla
2018	A*	`conf`	Streamlining Variational Inference for Constraint Satisfaction Problems. NeurIPS Aditya Grover, Tudor Achim, Stefano Ermon
2018	J	`jnl`	Streamlining Variational Inference for Constraint Satisfaction Problems. CoRR Aditya Grover, Tudor Achim, Stefano Ermon
2018	J	`jnl`	Uncertainty Autoencoders: Learning Compressed Representations via Variational Information Maximization. CoRR Aditya Grover, Stefano Ermon
2018	A	`conf`	Variational Rejection Sampling. AISTATS Aditya Grover, Ramki Gummadi, Miguel Lázaro-Gredilla, Dale Schuurmans, Stefano Ermon
2018	J	`jnl`	Variational Rejection Sampling. CoRR Aditya Grover, Ramki Gummadi, Miguel Lázaro-Gredilla, Dale Schuurmans, Stefano Ermon
2017	J	`jnl`	Boosted Generative Models. CoRR Aditya Grover, Stefano Ermon
2017	J	`jnl`	Flow-GAN: Bridging implicit and prescribed learning in generative models. CoRR Aditya Grover, Manik Dhar, Stefano Ermon
2016	A*	`conf`	Contextual Symmetries in Probabilistic Graphical Models. IJCAI Ankit Anand, Aditya Grover, Mausam, Parag Singla
2016	J	`jnl`	Contextual Symmetries in Probabilistic Graphical Models. CoRR Ankit Anand, Aditya Grover, Mausam, Parag Singla
2016	—	`conf`	Variational Bayes on Monte Carlo Steroids. NIPS Aditya Grover, Stefano Ermon
2016	A*	`conf`	node2vec: Scalable Feature Learning for Networks. KDD Aditya Grover, Jure Leskovec
2016	J	`jnl`	node2vec: Scalable Feature Learning for Networks. CoRR Aditya Grover, Jure Leskovec
2015	A*	`conf`	A Deep Hybrid Model for Weather Forecasting. KDD Aditya Grover, Ashish Kapoor, Eric Horvitz
2015	A	`conf`	A Novel Abstraction Framework for Online Planning: Extended Abstract. AAMAS Ankit Anand, Aditya Grover, Mausam, Parag Singla
2015	A*	`conf`	ASAP-UCT: Abstraction of State-Action Pairs in UCT. IJCAI Ankit Anand, Aditya Grover, Mausam, Parag Singla