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08/21/2023
Neural Amortized Inference for Nested Multi-agent Reasoning
Multi-agent interactions, such as communication, teaching, and bluffing,...
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08/18/2023
A Rank-One Optimization Framework and Its Applications to Transmit Beamforming
This paper proposes an elegant optimization framework consisting of a mi...
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06/28/2023
Federated Deep Reinforcement Learning-based Bitrate Adaptation for Dynamic Adaptive Streaming over HTTP
In video streaming over HTTP, the bitrate adaptation selects the quality...
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02/20/2023
Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments
Following up on our previous works, in this paper, we present Arena-Rosn...
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10/27/2022
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
The problem of inferring object shape from a single 2D image is undercon...
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06/12/2022
Arena-Bench: A Benchmarking Suite for Obstacle Avoidance Approaches in Highly Dynamic Environments
The ability to autonomously navigate safely, especially within dynamic e...
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06/03/2022
Drawing out of Distribution with Neuro-Symbolic Generative Models
Learning general-purpose representations from perceptual inputs is a hal...
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04/16/2021
Learning Evolved Combinatorial Symbols with a Neuro-symbolic Generative Model
Humans have the ability to rapidly understand rich combinatorial concept...
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07/06/2020
Learning to learn generative programs with Memoised Wake-Sleep
We study a class of neuro-symbolic generative models in which neural net...
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06/30/2020
Semi-supervised Sequential Generative Models
We introduce a novel objective for training deep generative time-series ...
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11/04/2019
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
We develop amortized population Gibbs (APG) samplers, a new class of aut...
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06/28/2019
The Thermodynamic Variational Objective
We introduce the thermodynamic variational objective (TVO) for learning ...
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03/12/2019
Imitation Learning of Factored Multi-agent Reactive Models
We apply recent advances in deep generative modeling to the task of imit...
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06/06/2018
Deep Variational Reinforcement Learning for POMDPs
Many real-world sequential decision making problems are partially observ...
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05/26/2018
Revisiting Reweighted Wake-Sleep
Discrete latent-variable models, while applicable in a variety of settin...
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03/13/2018
Secure Wireless Powered and Cooperative Jamming D2D Communications
This paper investigates a secure wireless-powered device-to-device (D2D)...
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03/04/2018
A Successive Optimization Approach to Pilot Design for Multi-Cell Massive MIMO Systems
In this letter, we introduce a novel pilot design approach that minimize...
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02/20/2018
Distributed Power Control in Downlink Cellular Massive MIMO Systems
This paper compares centralized and distributed methods to solve the pow...
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02/13/2018
Tighter Variational Bounds are Not Necessarily Better
We provide theoretical and empirical evidence that using tighter evidenc...
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12/21/2017
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
We consider the problem of Bayesian inference in the family of probabili...
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07/13/2017
Bayesian Optimization for Probabilistic Programs
We present the first general purpose framework for marginal maximum a po...
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05/29/2017
Auto-Encoding Sequential Monte Carlo
We introduce AESMC: a method for using deep neural networks for simultan...
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03/02/2017
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning
We draw a formal connection between using synthetic training data to opt...
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10/31/2016
Inference Compilation and Universal Probabilistic Programming
We introduce a method for using deep neural networks to amortize the cos...
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12/14/2015