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05/17/2023
Sparsity-depth Tradeoff in Infinitely Wide Deep Neural Networks
We investigate how sparse neural activity affects the generalization per...
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04/14/2023
EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks
Event-based sensors have recently drawn increasing interest in robotic p...
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01/27/2023
Policy-Value Alignment and Robustness in Search-based Multi-Agent Learning
Large-scale AI systems that combine search and learning have reached sup...
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06/14/2022
A theory of learning with constrained weight-distribution
A central question in computational neuroscience is how structure determ...
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09/14/2021
Object Shell Reconstruction: Camera-centric Object Representation for Robotic Grasping
Robots can effectively grasp and manipulate objects using their 3D model...
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06/21/2021
Curriculum-Driven Multi-Agent Learning and the Role of Implicit Communication in Teamwork
We propose a curriculum-driven learning strategy for solving difficult m...
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06/10/2021
Cooperative Multi-Agent Fairness and Equivariant Policies
We study fairness through the lens of cooperative multi-agent learning. ...
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06/05/2021
Local Disentanglement in Variational Auto-Encoders Using Jacobian L_1 Regularization
There have been many recent advances in representation learning; however...
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03/20/2021
Learning Continuous Cost-to-Go Functions for Non-holonomic Systems
This paper presents a supervised learning method to generate continuous ...
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12/10/2020
Cost-to-Go Function Generating Networks for High Dimensional Motion Planning
This paper presents c2g-HOF networks which learn to generate cost-to-go ...
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11/30/2020
Low-Bandwidth Communication Emerges Naturally in Multi-Agent Learning Systems
In this work, we study emergent communication through the lens of cooper...
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11/18/2020
Fast Motion Understanding with Spatiotemporal Neural Networks and Dynamic Vision Sensors
This paper presents a Dynamic Vision Sensor (DVS) based system for reaso...
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10/27/2020
Learning to Generate Cost-to-Go Functions for Efficient Motion Planning
Traditional motion planning is computationally burdensome for practical ...
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06/14/2020
Geodesic-HOF: 3D Reconstruction Without Cutting Corners
Single-view 3D object reconstruction is a challenging fundamental proble...
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04/03/2020
Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection
This paper presents a novel end-to-end system for pedestrian detection u...
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12/18/2019
Surface HOF: Surface Reconstruction from a Single Image Using Higher Order Function Networks
We address the problem of generating a high-resolution surface reconstru...
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10/23/2019
Learning Q-network for Active Information Acquisition
In this paper, we propose a novel Reinforcement Learning approach for so...
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10/04/2019
Higher Order Function Networks for View Planning and Multi-View Reconstruction
We consider the problem of planning views for a robot to acquire images ...
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07/24/2019
Higher-Order Function Networks for Learning Composable 3D Object Representations
We present a method to represent 3D objects using higher order functions...
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01/01/2019
Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning
In this paper, we introduce a new probabilistically safe local steering ...
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09/18/2018
U-Net for MAV-based Penstock Inspection: an Investigation of Focal Loss in Multi-class Segmentation for Corrosion Identification
Periodical inspection and maintenance of critical infrastructure such as...
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07/21/2018
Learning Optimal Resource Allocations in Wireless Systems
This paper considers the design of optimal resource allocation policies ...
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06/06/2018
Learning Implicit Sampling Distributions for Motion Planning
Sampling-based motion planners have experienced much success due to thei...
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05/22/2018
Nearest neighbor density functional estimation based on inverse Laplace transform
A general approach to L_2-consistent estimation of various density funct...
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05/22/2018
Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients
In this paper, we explore using deep reinforcement learning for problems...
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12/09/2017
Bayesian Q-learning with Assumed Density Filtering
While off-policy temporal difference methods have been broadly used in r...
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10/17/2017
Classification and Geometry of General Perceptual Manifolds
Perceptual manifolds arise when a neural population responds to an ensem...
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09/17/2017
Memory Augmented Control Networks
Planning problems in partially observable environments cannot be solved ...
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05/28/2017
Learning Data Manifolds with a Cutting Plane Method
We consider the problem of classifying data manifolds where each manifol...
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12/06/2015
Linear Readout of Object Manifolds
Objects are represented in sensory systems by continuous manifolds due t...
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05/26/2015
Belief Flows of Robust Online Learning
This paper introduces a new probabilistic model for online learning whic...
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04/22/2014
An Adversarial Interpretation of Information-Theoretic Bounded Rationality
Recently, there has been a growing interest in modeling planning with in...
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09/19/2011