Xi Chen - RankMe

56 papers A* 11A 2Journal 31Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching. CoRR Zhen Wu, Xiaoyu Huang, Lujie Yang, Yuanhang Zhang, Koushil Sreenath, Xi Chen, Pieter Abbeel, Rocky Duan, Angjoo Kanazawa, Carmelo Sferrazza, Guanya Shi, C. Karen Liu
2024	A*	`conf`	Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs. ICRA Nikhil Mishra, Maximilian Sieb, Pieter Abbeel, Xi Chen
2024	J	`jnl`	Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs. CoRR Nikhil Mishra, Maximilian Sieb, Pieter Abbeel, Xi Chen
2023	A	`conf`	Convolutional Occupancy Models for Dense Packing of Complex, Novel Objects. IROS Nikhil Mishra, Pieter Abbeel, Xi Chen, Maximilian Sieb
2023	J	`jnl`	Convolutional Occupancy Models for Dense Packing of Complex, Novel Objects. CoRR Nikhil Mishra, Pieter Abbeel, Xi Chen, Maximilian Sieb
2023	A*	`conf`	Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN. ICRA Yuxuan Liu, Nikhil Mishra, Pieter Abbeel, Xi Chen
2023	J	`jnl`	Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN. CoRR Yuxuan Liu, Nikhil Mishra, Pieter Abbeel, Xi Chen
2023	A	`conf`	Self-Supervised Instance Segmentation by Grasping. IROS Yuxuan Liu, Xi Chen, Pieter Abbeel
2023	J	`jnl`	Self-Supervised Instance Segmentation by Grasping. CoRR Yuxuan Liu, Xi Chen, Pieter Abbeel
2022	—	`conf`	Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction. ECCV (10) Yuxuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen
2022	J	`jnl`	Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction. CoRR Yuxuan Liu, Nikhil Mishra, Maximilian Sieb, Yide Shentu, Pieter Abbeel, Xi Chen
2020	J	`jnl`	NeuroCard: One Cardinality Estimator for All Tables. CoRR Zongheng Yang, Amog Kamsetty, Sifei Luan, Eric Liang, Yan Duan, Xi Chen, Ion Stoica
2020	J	`jnl`	NeuroCard: One Cardinality Estimator for All Tables. Proc. VLDB Endow. Zongheng Yang, Amog Kamsetty, Sifei Luan, Eric Liang, Yan Duan, Xi Chen, Ion Stoica
2020	A*	`conf`	Variable Skipping for Autoregressive Range Density Estimation. ICML Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen
2020	J	`jnl`	Variable Skipping for Autoregressive Range Density Estimation. CoRR Eric Liang, Zongheng Yang, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen
2019	J	`jnl`	Deep Unsupervised Cardinality Estimation. Proc. VLDB Endow. Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
2019	A*	`conf`	Evaluating Protein Transfer Learning with TAPE. NeurIPS Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John F. Canny, Pieter Abbeel, Yun S. Song
2019	J	`jnl`	Evaluating Protein Transfer Learning with TAPE. CoRR Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John F. Canny, Pieter Abbeel, Yun S. Song
2019	A*	`conf`	Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. ICML Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
2019	J	`jnl`	Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. CoRR Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
2019	A*	`conf`	Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. ICML Daniel Ho, Eric Liang, Xi Chen, Ion Stoica, Pieter Abbeel
2019	J	`jnl`	Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. CoRR Daniel Ho, Eric Liang, Ion Stoica, Pieter Abbeel, Xi Chen
2019	J	`jnl`	Selectivity Estimation with Deep Likelihood Models. CoRR Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica
2018	—	`conf`	A Simple Neural Attentive Meta-Learner. ICLR (Poster) Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, Pieter Abbeel
2018	A*	`conf`	Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation. ICRA Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, Pieter Abbeel
2018	—	`conf`	Meta Learning Shared Hierarchies. ICLR (Poster) Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman
2018	—	`conf`	Parameter Space Noise for Exploration. ICLR (Poster) Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz
2018	—	`conf`	PixelSNAIL: An Improved Autoregressive Generative Model. ICLR (Workshop) Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel
2018	A*	`conf`	PixelSNAIL: An Improved Autoregressive Generative Model. ICML Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel
2018	J	`jnl`	Some Considerations on Learning to Explore via Meta-Reinforcement Learning. CoRR Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
2018	A*	`conf`	The Importance of Sampling inMeta-Reinforcement Learning. NeurIPS Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
2017	—	`conf`	#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. NIPS Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
2017	J	`jnl`	A K-fold Method for Baseline Estimation in Policy Gradient Algorithms. CoRR Nithyanand Kota, Abhishek Mishra, Sunil Srinivasa, Xi Chen, Pieter Abbeel
2017	J	`jnl`	Equivalence Between Policy Gradients and Soft Q-Learning. CoRR John Schulman, Pieter Abbeel, Xi Chen
2017	J	`jnl`	Evolution Strategies as a Scalable Alternative to Reinforcement Learning. CoRR Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever
2017	J	`jnl`	Meta Learning Shared Hierarchies. CoRR Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman
2017	J	`jnl`	Meta-Learning with Temporal Convolutions. CoRR Nikhil Mishra, Mostafa Rohaninejad, Xi Chen, Pieter Abbeel
2017	J	`jnl`	Parameter Space Noise for Exploration. CoRR Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz
2017	—	`conf`	PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. ICLR (Poster) Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma
2017	J	`jnl`	PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. CoRR Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma
2017	J	`jnl`	PixelSNAIL: An Improved Autoregressive Generative Model. CoRR Xi Chen, Nikhil Mishra, Mostafa Rohaninejad, Pieter Abbeel
2017	J	`jnl`	Safer Classification by Synthesis. CoRR William Wang, Angelina Wang, Aviv Tamar, Xi Chen, Pieter Abbeel
2017	—	`conf`	Variational Lossy Autoencoder. ICLR (Poster) Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
2016	J	`jnl`	#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. CoRR Haoran Tang, Rein Houthooft, Davis Foote, Adam Stooke, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
2016	A*	`conf`	Benchmarking Deep Reinforcement Learning for Continuous Control. ICML Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel
2016	J	`jnl`	Benchmarking Deep Reinforcement Learning for Continuous Control. CoRR Yan Duan, Xi Chen, Rein Houthooft, John Schulman, Pieter Abbeel
2016	J	`jnl`	Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks. CoRR Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
2016	—	`conf`	Improved Techniques for Training GANs. NIPS Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	J	`jnl`	Improved Techniques for Training GANs. CoRR Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
2016	—	`conf`	Improving Variational Autoencoders with Inverse Autoregressive Flow. NIPS Diederik P. Kingma, Tim Salimans, Rafal Józefowicz, Xi Chen, Ilya Sutskever, Max Welling
2016	—	`conf`	InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. NIPS Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel
2016	J	`jnl`	InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. CoRR Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel
2016	J	`jnl`	RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning. CoRR Yan Duan, John Schulman, Xi Chen, Peter L. Bartlett, Ilya Sutskever, Pieter Abbeel
2016	—	`conf`	VIME: Variational Information Maximizing Exploration. NIPS Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, Pieter Abbeel
2016	J	`jnl`	Variational Lossy Autoencoder. CoRR Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
2015	A*	`conf`	Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing. ICML Yasin Abbasi-Yadkori, Peter L. Bartlett, Xi Chen, Alan Malek