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07/15/2023
Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
Robustness has been extensively studied in reinforcement learning (RL) t...
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06/15/2023
Your Room is not Private: Gradient Inversion Attack for Deep Q-Learning
The prominence of embodied Artificial Intelligence (AI), which empowers ...
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05/18/2023
Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models
Recently, reward-conditioned reinforcement learning (RCRL) has gained po...
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04/29/2023
Critical Scenario Generation for Developing Trustworthy Autonomy
Autonomous systems, such as self-driving vehicles, quadrupeds, and robot...
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01/23/2023
Learning to View: Decision Transformers for Active Object Detection
Active perception describes a broad class of techniques that couple plan...
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09/16/2022
Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability
A trustworthy reinforcement learning algorithm should be competent in so...
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07/19/2022
Generalizing Goal-Conditioned Reinforcement Learning with Variational Causal Reasoning
As a pivotal component to attaining generalizable solutions in human int...
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06/20/2022
SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles
As shown by recent studies, machine intelligence-enabled systems are vul...
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02/04/2022
A Survey on Safety-Critical Driving Scenario Generation – A Methodological Perspective
Autonomous driving systems have witnessed a significant development duri...
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11/03/2021
Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems
Rare-event simulation techniques, such as importance sampling (IS), cons...
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10/26/2021
CausalAF: Causal Autoregressive Flow for Goal-Directed Safety-Critical Scenes Generation
Goal-directed generation, aiming for solving downstream tasks by generat...
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06/08/2021
Semantically Controllable Scene Generation with Guidance of Explicit Knowledge
Deep Generative Models (DGMs) are known for their superior capability in...
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01/02/2021
Context-Aware Safe Reinforcement Learning for Non-Stationary Environments
Safety is a critical concern when deploying reinforcement learning agent...
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09/16/2020
Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation
Existing neural network-based autonomous systems are shown to be vulnera...
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06/28/2020
Deep Probabilistic Accelerated Evaluation: A Certifiable Rare-Event Simulation Methodology for Black-Box Autonomy
Evaluating the reliability of intelligent physical systems against rare ...
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06/19/2020
Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes
Continuously learning to solve unseen tasks with limited experience has ...
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03/02/2020
Learning to Collide: An Adaptive Safety-Critical Scenarios Generating Method
Long-tail and rare event problems become crucial when autonomous driving...
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11/15/2019
Adaptive Multi-scale Detection of Acoustic Events
The goal of acoustic (or sound) events detection (AED or SED) is to pred...
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09/17/2019
CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarios
Naturalistic driving trajectories are crucial for the performance of aut...
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03/29/2019
Multi-Scale Time-Frequency Attention for Rare Sound Event Detection
Attention mechanism has been widely applied to various sound-related tas...
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09/15/2018
Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters
Generating multi-vehicle trajectories analogous to these in real world c...
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07/14/2018
Hierarchical Reinforcement Learning Framework towards Multi-agent Navigation
This paper proposes a navigation algorithm ori- ented to multi-agent dyn...
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03/24/2018
MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks
In this paper, we propose an enhanced triplet method that improves the e...
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02/10/2018
Vehicle Pose and Shape Estimation through Multiple Monocular Vision
In this paper, we present an accurate approach to estimate vehicles' pos...
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02/10/2018
