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06/07/2023
Autonomous Capability Assessment of Black-Box Sequential Decision-Making Systems
It is essential for users to understand what their AI systems can and ca...
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12/18/2022
Predicting Citi Bike Demand Evolution Using Dynamic Graphs
Bike sharing systems often suffer from poor capacity management as a res...
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12/06/2022
Hierarchical Termination Analysis for Generalized Planning
This paper presents a new approach for analyzing and identifying potenti...
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10/04/2022
Learning Dynamic Abstract Representations for Sample-Efficient Reinforcement Learning
In many real-world problems, the learning agent needs to learn a problem...
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09/30/2022
Multi-Task Option Learning and Discovery for Stochastic Path Planning
This paper addresses the problem of reliably and efficiently solving bro...
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04/27/2022
Relational Abstractions for Generalized Reinforcement Learning on Symbolic Problems
Reinforcement learning in problems with symbolic state spaces is challen...
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04/08/2022
Preliminary Results on Using Abstract AND-OR Graphs for Generalized Solving of Stochastic Shortest Path Problems
Several goal-oriented problems in the real-world can be naturally expres...
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03/24/2022
Differential Assessment of Black-Box AI Agents
Much of the research on learning symbolic models of AI agents focuses on...
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02/02/2022
Using Deep Learning to Bootstrap Abstractions for Hierarchical Robot Planning
This paper addresses the problem of learning abstractions that boost rob...
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11/15/2021
Beyond Mono to Binaural: Generating Binaural Audio from Mono Audio with Depth and Cross Modal Attention
Binaural audio gives the listener an immersive experience and can enhanc...
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10/31/2021
JEDAI Explains Decision-Making AI
This paper presents JEDAI, an AI system designed for outreach and educat...
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09/28/2021
Joint Communication and Motion Planning for Cobots
The increasing deployment of robots in co-working scenarios with humans ...
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08/28/2021
Anytime Stochastic Task and Motion Policies
In order to solve complex, long-horizon tasks, intelligent robots need t...
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08/21/2021
Learning Causal Models of Autonomous Agents using Interventions
One of the several obstacles in the widespread use of AI systems is the ...
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08/10/2021
Depth Infused Binaural Audio Generation using Hierarchical Cross-Modal Attention
Binaural audio gives the listener the feeling of being in the recording ...
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07/28/2021
Learning User-Interpretable Descriptions of Black-Box AI System Capabilities
Several approaches have been developed to answer specific questions that...
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05/02/2021
Planning for Proactive Assistance in Environments with Partial Observability
This paper addresses the problem of synthesizing the behavior of an AI a...
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03/28/2021
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
We propose simple yet effective improvements in point representations an...
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03/15/2021
Beyond Image to Depth: Improving Depth Prediction using Echoes
We address the problem of estimating depth with multi modal audio visual...
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12/01/2020
Learning Sampling Distributions for Efficient High-Dimensional Motion Planning
Robot motion planning involves computing a sequence of valid robot confi...
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07/10/2020
Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning
Computing goal-directed behavior (sequential decision-making, or plannin...
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02/04/2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Black Box Simulators
As more and more complex AI systems are introduced into our day-to-day l...
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12/29/2019
Learning Generalized Models by Interrogating Black-Box Autonomous Agents
This paper develops a new approach for estimating the internal model of ...
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05/25/2019
Balancing Goal Obfuscation and Goal Legibility in Settings with Cooperative and Adversarial Observers
In order to be useful in the real world, AI agents need to plan and act ...
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04/30/2019
Anytime Integrated Task and Motion Policies for Stochastic Environments
In order to solve complex, long-horizon tasks, intelligent robots need t...
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04/17/2019
Few Shot Speaker Recognition using Deep Neural Networks
The recent advances in deep learning are mostly driven by availability o...
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04/17/2019
An Online Learning Approach for Dengue Fever Classification
This paper introduces a novel approach for dengue fever classification b...
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03/27/2019
DeepPoint3D: Learning Discriminative Local Descriptors using Deep Metric Learning on 3D Point Clouds
Learning local descriptors is an important problem in computer vision. W...
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03/19/2019
Why Couldn't You do that? Explaining Unsolvability of Classical Planning Problems in the Presence of Plan Advice
Explainable planning is widely accepted as a prerequisite for autonomous...
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03/08/2019
Identifying Critical Regions for Motion Planning using Auto-Generated Saliency Labels with Convolutional Neural Networks
In this paper, we present a new approach to learning for motion planning...
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06/06/2018
Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Despite the recent successes of probabilistic programming languages (PPL...
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06/06/2018
On Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms
Despite of the recent successes of probabilistic programming languages (...
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02/19/2018
Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations
There is a growing interest within the AI research community to develop ...
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02/16/2018
Implicit Robot-Human Communication in Adversarial and Collaborative Environments
Users of AI systems may rely upon them to produce plans for achieving de...
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02/16/2018
An Anytime Algorithm for Task and Motion MDPs
Integrated task and motion planning has emerged as a challenging problem...
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12/04/2017
Enhanced Characterness for Text Detection in the Wild
Text spotting is an interesting research problem as text may appear at a...
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12/04/2017
Object Classification using Ensemble of Local and Deep Features
In this paper we propose an ensemble of local and deep features for obje...
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10/17/2017
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
We introduce a large-scale 3D shape understanding benchmark using data a...
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09/21/2017
Drought Stress Classification using 3D Plant Models
Quantification of physiological changes in plants can capture different ...
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08/26/2017
3D Binary Signatures
In this paper, we propose a novel binary descriptor for 3D point clouds....
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08/24/2017
Learning Generalized Reactive Policies using Deep Neural Networks
We consider the problem of learning for planning, where knowledge acquir...
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01/22/2017
Large Scale Novel Object Discovery in 3D
We present a method for discovering objects in 3D point clouds from sens...
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04/25/2015