Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing. - Yasin Abbasi-Yadkori; Peter L. Bartlett; Xi Chen 022; Alan Malek (ICML, 2015)

Benchmarking Deep Reinforcement Learning for Continuous Control. - Yan Duan; Xi Chen 022; Rein Houthooft; John Schulman; Pieter Abbeel (ICML, 2016)

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets. - Xi Chen 022; Yan Duan; Rein Houthooft; John Schulman; Ilya Sutskever; Pieter Abbeel (NIPS, 2016)

VIME: Variational Information Maximizing Exploration. - Rein Houthooft; Xi Chen 022; Yan Duan; John Schulman; Filip De Turck; Pieter Abbeel (NIPS, 2016)

Improving Variational Autoencoders with Inverse Autoregressive Flow. - Diederik P. Kingma; Tim Salimans; Rafal Józefowicz; Xi Chen 022; Ilya Sutskever; Max Welling (NIPS, 2016)

Improved Techniques for Training GANs. - Tim Salimans; Ian J. Goodfellow; Wojciech Zaremba; Vicki Cheung; Alec Radford; Xi Chen 022 (NIPS, 2016)

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning. - Yan Duan; John Schulman; Xi Chen 022; Peter L. Bartlett; Ilya Sutskever; Pieter Abbeel (CoRR, 2016)

Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks. - Rein Houthooft; Xi Chen 022; Yan Duan; John Schulman; Filip De Turck; Pieter Abbeel (CoRR, 2016)

Variational Lossy Autoencoder. - Xi Chen 022; Diederik P. Kingma; Tim Salimans; Yan Duan; Prafulla Dhariwal; John Schulman; Ilya Sutskever; Pieter Abbeel (ICLR (Poster), 2017)

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. - Tim Salimans; Andrej Karpathy; Xi Chen 022; Diederik P. Kingma (ICLR (Poster), 2017)

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning. - Haoran Tang; Rein Houthooft; Davis Foote; Adam Stooke; Xi Chen 022; Yan Duan; John Schulman; Filip De Turck; Pieter Abbeel (NIPS, 2017)

A K-fold Method for Baseline Estimation in Policy Gradient Algorithms. - Nithyanand Kota; Abhishek Mishra; Sunil Srinivasa; Xi Chen 022; Pieter Abbeel (CoRR, 2017)

Meta-Learning with Temporal Convolutions. - Nikhil Mishra; Mostafa Rohaninejad; Xi Chen 022; Pieter Abbeel (CoRR, 2017)

Evolution Strategies as a Scalable Alternative to Reinforcement Learning. - Tim Salimans; Jonathan Ho; Xi Chen 022; Ilya Sutskever (CoRR, 2017)

Equivalence Between Policy Gradients and Soft Q-Learning. - John Schulman; Pieter Abbeel; Xi Chen 022 (CoRR, 2017)

Safer Classification by Synthesis. - William Wang; Angelina Wang; Aviv Tamar; Xi Chen 022; Pieter Abbeel (CoRR, 2017)

Meta Learning Shared Hierarchies. - Kevin Frans; Jonathan Ho; Xi Chen 022; Pieter Abbeel; John Schulman (ICLR (Poster), 2018)

A Simple Neural Attentive Meta-Learner. - Nikhil Mishra; Mostafa Rohaninejad; Xi Chen 022; Pieter Abbeel (ICLR (Poster), 2018)

Parameter Space Noise for Exploration. - Matthias Plappert; Rein Houthooft; Prafulla Dhariwal; Szymon Sidor; Richard Y. Chen; Xi Chen 022; Tamim Asfour; Pieter Abbeel; Marcin Andrychowicz (ICLR (Poster), 2018)

PixelSNAIL: An Improved Autoregressive Generative Model. - Xi Chen 022; Nikhil Mishra; Mostafa Rohaninejad; Pieter Abbeel (ICML, 2018)

Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation. - Tianhao Zhang 001; Zoe McCarthy; Owen Jow; Dennis Lee 003; Xi Chen 022; Ken Goldberg; Pieter Abbeel (ICRA, 2018)

The Importance of Sampling inMeta-Reinforcement Learning. - Bradly C. Stadie; Ge Yang 003; Rein Houthooft; Xi Chen 022; Yan Duan; Yuhuai Wu; Pieter Abbeel; Ilya Sutskever (NeurIPS, 2018)

Some Considerations on Learning to Explore via Meta-Reinforcement Learning. - Bradly C. Stadie; Ge Yang 003; Rein Houthooft; Xi Chen 022; Yan Duan; Yuhuai Wu; Pieter Abbeel; Ilya Sutskever (CoRR, 2018)

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. - Jonathan Ho; Xi Chen 022; Aravind Srinivas; Yan Duan; Pieter Abbeel (ICML, 2019)

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules. - Daniel Ho; Eric Liang; Xi Chen 022; Ion Stoica; Pieter Abbeel (ICML, 2019)

Evaluating Protein Transfer Learning with TAPE. - Roshan Rao; Nicholas Bhattacharya; Neil Thomas; Yan Duan; Xi Chen 022; John F. Canny; Pieter Abbeel; Yun S. Song (NeurIPS, 2019)

Selectivity Estimation with Deep Likelihood Models. - Zongheng Yang; Eric Liang; Amog Kamsetty; Chenggang Wu 001; Yan Duan; Xi Chen 022; Pieter Abbeel; Joseph M. Hellerstein; Sanjay Krishnan; Ion Stoica (CoRR, 2019)

Deep Unsupervised Cardinality Estimation. - Zongheng Yang; Eric Liang; Amog Kamsetty; Chenggang Wu 001; Yan Duan; Xi Chen 022; Pieter Abbeel; Joseph M. Hellerstein; Sanjay Krishnan; Ion Stoica (Proc. VLDB Endow., 2019)

Variable Skipping for Autoregressive Range Density Estimation. - Eric Liang; Zongheng Yang; Ion Stoica; Pieter Abbeel; Yan Duan; Xi Chen 022 (ICML, 2020)

NeuroCard: One Cardinality Estimator for All Tables. - Zongheng Yang; Amog Kamsetty; Sifei Luan 001; Eric Liang; Yan Duan; Xi Chen 022; Ion Stoica (Proc. VLDB Endow., 2020)

Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction. - Yuxuan Liu 001; Nikhil Mishra; Maximilian Sieb; Yide Shentu; Pieter Abbeel; Xi Chen 022 (ECCV (10), 2022)

Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN. - Yuxuan Liu 001; Nikhil Mishra; Pieter Abbeel; Xi Chen 022 (ICRA, 2023)

Self-Supervised Instance Segmentation by Grasping. - Yuxuan Liu 001; Xi Chen 022; Pieter Abbeel (IROS, 2023)

Convolutional Occupancy Models for Dense Packing of Complex, Novel Objects. - Nikhil Mishra; Pieter Abbeel; Xi Chen 022; Maximilian Sieb (IROS, 2023)

Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs. - Nikhil Mishra; Maximilian Sieb; Pieter Abbeel; Xi Chen 022 (ICRA, 2024)