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09/16/2023
GRaCE: Optimizing Grasps to Satisfy Ranked Criteria in Complex Scenarios
This paper addresses the multi-faceted problem of robot grasping, where ...
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08/14/2023
Refining 6-DoF Grasps with Context-Specific Classifiers
In this work, we present GraspFlow, a refinement approach for generating...
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08/12/2023
Latent Emission-Augmented Perspective-Taking (LEAPT) for Human-Robot Interaction
Perspective-taking is the ability to perceive or understand a situation ...
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06/22/2023
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities
There is increasing attention being given to how to regulate AI systems....
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05/17/2023
Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models
The recent proliferation of large-scale text-to-image models has led to ...
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03/07/2023
Generative Modeling with Flow-Guided Density Ratio Learning
We present Flow-Guided Density Ratio Learning (FDRL), a simple and scala...
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03/06/2023
Large Language Models as Zero-Shot Human Models for Human-Robot Interaction
Human models play a crucial role in human-robot interaction (HRI), enabl...
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02/10/2023
Translating Natural Language to Planning Goals with Large-Language Models
Recent large language models (LLMs) have demonstrated remarkable perform...
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01/26/2023
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
Learning accurate predictive models of real-world dynamic phenomena (e.g...
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01/12/2023
Heterogeneous Beliefs and Multi-Population Learning in Network Games
The effect of population heterogeneity in multi-agent learning is practi...
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11/10/2022
Safety-Constrained Policy Transfer with Successor Features
In this work, we focus on the problem of safe policy transfer in reinfor...
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10/13/2022
Observed Adversaries in Deep Reinforcement Learning
In this work, we point out the problem of observed adversaries for deep ...
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09/22/2022
SCALES: From Fairness Principles to Constrained Decision-Making
This paper proposes SCALES, a general framework that translates well-est...
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03/06/2022
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication
Communication is a hallmark of intelligence. In this work, we present MI...
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03/03/2022
The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model
Although learning has found wide application in multi-agent systems, its...
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10/26/2021
Deep Explicit Duration Switching Models for Time Series
Many complex time series can be effectively subdivided into distinct reg...
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07/06/2021
Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning
This work focuses on learning useful and robust deep world models using ...
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06/01/2021
Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects
Humans display the remarkable ability to sense the world through tools a...
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12/01/2020
Refining Deep Generative Models via Wasserstein Gradient Flows
Deep generative modeling has seen impressive advances in recent years, t...
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11/17/2020
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
The problem of inverse reinforcement learning (IRL) is relevant to a var...
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09/15/2020
Event-Driven Visual-Tactile Sensing and Learning for Robots
This work contributes an event-driven visual-tactile perception system, ...
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08/03/2020
Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration
Common experience suggests that agents who know each other well are bett...
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08/01/2020
TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition
Tactile perception is crucial for a variety of robot tasks including gra...
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06/29/2020
The Evolutionary Dynamics of Independent Learning Agents in Population Games
Understanding the evolutionary dynamics of reinforcement learning under ...
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05/08/2020
ST-MNIST – The Spiking Tactile MNIST Neuromorphic Dataset
Tactile sensing is an essential modality for smart robots as it enables ...
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09/16/2019
A Characteristic Function Approach to Deep Implicit Generative Modeling
In this paper, we formulate the problem of learning an Implicit Generati...
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09/03/2019
Embedding Symbolic Knowledge into Deep Networks
In this work, we aim to leverage prior symbolic knowledge to improve the...
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09/03/2019
Semantically-Regularized Logic Graph Embeddings
In this work, we aim to utilize prior knowledge encoded as logical rules...
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09/03/2019
Robot Capability and Intention in Trust-based Decisions across Tasks
In this paper, we present results from a human-subject study designed to...
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05/30/2019
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series
Integrating deep learning with latent state space models has the potenti...
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03/15/2019
Applying Probabilistic Programming to Affective Computing
Affective Computing is a rapidly growing field spurred by advancements i...
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09/12/2018
Hyperprior Induced Unsupervised Disentanglement of Latent Representations
We address the problem of unsupervised disentanglement of latent represe...
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08/02/2018
Generation Meets Recommendation: Proposing Novel Items for Groups of Users
Consider a movie studio aiming to produce a set of new movies for summer...
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07/05/2018
The Transfer of Human Trust in Robot Capabilities across Tasks
Trust is crucial in shaping human interactions with one another and with...
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01/12/2018