Xi Chen

Affiliations:
  • covariant.ai, Emeryville, CA, USA
  • University of California Berkeley, Department of Electrical Engineering and Computer Sciences, Berkeley, CA, USA


According to our database1, Xi Chen authored at least 35 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Convolutional Occupancy Models for Dense Packing of Complex, Novel Objects.
IROS, 2023

Self-Supervised Instance Segmentation by Grasping.
IROS, 2023

Distributional Instance Segmentation: Modeling Uncertainty and High Confidence Predictions with Latent-MaskRCNN.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
Autoregressive Uncertainty Modeling for 3D Bounding Box Prediction.
Proceedings of the Computer Vision - ECCV 2022, 2022

2020
NeuroCard: One Cardinality Estimator for All Tables.
Proc. VLDB Endow., 2020

Variable Skipping for Autoregressive Range Density Estimation.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Deep Unsupervised Cardinality Estimation.
Proc. VLDB Endow., 2019

Selectivity Estimation with Deep Likelihood Models.
CoRR, 2019

Evaluating Protein Transfer Learning with TAPE.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules.
Proceedings of the 36th International Conference on Machine Learning, 2019

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Some Considerations on Learning to Explore via Meta-Reinforcement Learning.
CoRR, 2018

The Importance of Sampling inMeta-Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

PixelSNAIL: An Improved Autoregressive Generative Model.
Proceedings of the 35th International Conference on Machine Learning, 2018

Parameter Space Noise for Exploration.
Proceedings of the 6th International Conference on Learning Representations, 2018

A Simple Neural Attentive Meta-Learner.
Proceedings of the 6th International Conference on Learning Representations, 2018

Meta Learning Shared Hierarchies.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Safer Classification by Synthesis.
CoRR, 2017

Equivalence Between Policy Gradients and Soft Q-Learning.
CoRR, 2017

Evolution Strategies as a Scalable Alternative to Reinforcement Learning.
CoRR, 2017

Meta-Learning with Temporal Convolutions.
CoRR, 2017

A K-fold Method for Baseline Estimation in Policy Gradient Algorithms.
CoRR, 2017

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications.
Proceedings of the 5th International Conference on Learning Representations, 2017

Variational Lossy Autoencoder.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks.
CoRR, 2016

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning.
CoRR, 2016

Improved Techniques for Training GANs.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improving Variational Autoencoders with Inverse Autoregressive Flow.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

VIME: Variational Information Maximizing Exploration.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Benchmarking Deep Reinforcement Learning for Continuous Control.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Large-Scale Markov Decision Problems with KL Control Cost and its Application to Crowdsourcing.
Proceedings of the 32nd International Conference on Machine Learning, 2015


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