MIT

∙ Cambridge , United States ∙ 0 followers

The Massachusetts Institute of Technology is a private research university in Cambridge, Massachusetts.

Featured Researchers

Wei Wang
225 publications
Yu Zhang
177 publications
Ruslan Salakhutdinov
126 publications
Hao Wang
125 publications
Yue Wang
100 publications
Anima Anandkumar
96 publications
Jie Chen
91 publications
Joshua B. Tenenbaum
85 publications
Zheng Zhang
85 publications
James Glass
85 publications
Antonio Torralba
81 publications

The Computational Limits of Deep Learning

Deep learning's recent history has been one of achievement: from triumph...
07/10/2020 ∙ by Neil C. Thompson, et al. ∙ 377 ∙ share

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Understanding Human Judgments of Causality

Discriminating between causality and correlation is a major problem in m...
12/19/2019 ∙ by Masahiro Kazama, et al. ∙ 100 ∙ share

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The Synthesizability of Molecules Proposed by Generative Models

The discovery of functional molecules is an expensive and time-consuming...
02/17/2020 ∙ by Wenhao Gao, et al. ∙ 83 ∙ share

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Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization

While deep learning is successful in a number of applications, it is not...
08/25/2019 ∙ by Tomaso Poggio, et al. ∙ 82 ∙ share

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Learning to Localize Sound Sources in Visual Scenes: Analysis and Applications

Visual events are usually accompanied by sounds in our daily lives. Howe...
11/20/2019 ∙ by Arda Senocak, et al. ∙ 65 ∙ share

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Interpretable Neuroevolutionary Models for Learning Non-Differentiable Functions and Programs

A key factor in the modern success of deep learning is the astonishing e...
07/16/2020 ∙ by Allan Costa, et al. ∙ 50 ∙ share

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Generalized Maximum Causal Entropy for Inverse Reinforcement Learning

We consider the problem of learning from demonstrated trajectories with ...
11/16/2019 ∙ by Tien Mai, et al. ∙ 44 ∙ share

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A Probe into Understanding GAN and VAE models

Both generative adversarial network models and variational autoencoders ...
12/13/2018 ∙ by Jingzhao Zhang, et al. ∙ 38 ∙ share

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Data augmentation using learned transforms for one-shot medical image segmentation

Biomedical image segmentation is an important task in many medical appli...
02/25/2019 ∙ by Amy Zhao, et al. ∙ 33 ∙ share

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A Theory of Uncertainty Variables for State Estimation and Inference

Probability theory forms an overarching framework for modeling uncertain...
09/24/2019 ∙ by Rajat Talak, et al. ∙ 32 ∙ share

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Survey of Attacks and Defenses on Edge-Deployed Neural Networks

Deep Neural Network (DNN) workloads are quickly moving from datacenters ...
11/27/2019 ∙ by Mihailo Isakov, et al. ∙ 30 ∙ share

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Avoidance Learning Using Observational Reinforcement Learning

Imitation learning seeks to learn an expert policy from sampled demonstr...
09/24/2019 ∙ by David Venuto, et al. ∙ 29 ∙ share

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DiffTaichi: Differentiable Programming for Physical Simulation

We study the problem of learning and optimizing through physical simulat...
10/01/2019 ∙ by Yuanming Hu, et al. ∙ 29 ∙ share

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Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

We provide an open-source C++ library for real-time metric-semantic visu...
10/06/2019 ∙ by Antoni Rosinol, et al. ∙ 28 ∙ share

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Compositional Explanations of Neurons

We describe a procedure for explaining neurons in deep representations b...
06/24/2020 ∙ by Jesse Mu, et al. ∙ 28 ∙ share

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Continual Learning with Self-Organizing Maps

Despite remarkable successes achieved by modern neural networks in a wid...
04/19/2019 ∙ by Pouya Bashivan, et al. ∙ 26 ∙ share

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Inverse Reinforcement Learning with Missing Data

We consider the problem of recovering an expert's reward function with i...
11/16/2019 ∙ by Tien Mai, et al. ∙ 26 ∙ share

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Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization

Domain generalization is the problem of machine learning when the traini...
02/13/2020 ∙ by Vikas K. Garg, et al. ∙ 26 ∙ share

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Uncertainty Quantification Using Neural Networks for Molecular Property Prediction

Uncertainty quantification (UQ) is an important component of molecular p...
05/20/2020 ∙ by Lior Hirschfeld, et al. ∙ 25 ∙ share

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3D Traffic Simulation for Autonomous Vehicles in Unity and Python

Over the recent years, there has been an explosion of studies on autonom...
10/30/2018 ∙ by Zhijing Jin, et al. ∙ 24 ∙ share

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On Fast Leverage Score Sampling and Optimal Learning

Leverage score sampling provides an appealing way to perform approximate...
10/31/2018 ∙ by Alessandro Rudi, et al. ∙ 24 ∙ share

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Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling

We consider the problem of inferring the values of an arbitrary set of v...
02/06/2019 ∙ by Hao Wang, et al. ∙ 24 ∙ share

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Are Transformers universal approximators of sequence-to-sequence functions?

Despite the widespread adoption of Transformer models for NLP tasks, the...
12/20/2019 ∙ by Chulhee Yun, et al. ∙ 24 ∙ share

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Federated Visual Classification with Real-World Data Distribution

Federated Learning enables visual models to be trained on-device, bringi...
03/18/2020 ∙ by Tzu Ming Harry Hsu, et al. ∙ 24 ∙ share

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Adversarial Genetic Programming for Cyber Security: A Rising Application Domain Where GP Matters

Cyber security adversaries and engagements are ubiquitous and ceaseless....
04/07/2020 ∙ by Una-May O'Reilly, et al. ∙ 24 ∙ share

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HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

Transformers are ubiquitous in Natural Language Processing (NLP) tasks, ...
05/28/2020 ∙ by Hanrui Wang, et al. ∙ 24 ∙ share

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Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning

Learning robotic manipulation tasks using reinforcement learning with sp...
12/23/2019 ∙ by Richard Li, et al. ∙ 23 ∙ share

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How do Data Science Workers Collaborate? Roles, Workflows, and Tools

Today, the prominence of data science within organizations has given ris...
01/18/2020 ∙ by Amy X. Zhang, et al. ∙ 23 ∙ share

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The Limitations of Adversarial Training and the Blind-Spot Attack

The adversarial training procedure proposed by Madry et al. (2018) is on...
01/15/2019 ∙ by Huan Zhang, et al. ∙ 22 ∙ share

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Speech2Face: Learning the Face Behind a Voice

How much can we infer about a person's looks from the way they speak? In...
05/23/2019 ∙ by Tae-Hyun Oh, et al. ∙ 22 ∙ share

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Learning with AMIGo: Adversarially Motivated Intrinsic Goals

A key challenge for reinforcement learning (RL) consists of learning in ...
06/22/2020 ∙ by Andres Campero, et al. ∙ 22 ∙ share

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Verifiably Safe Exploration for End-to-End Reinforcement Learning

Deploying deep reinforcement learning in safety-critical settings requir...
07/02/2020 ∙ by Nathan Hunt, et al. ∙ 22 ∙ share

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Observational Overfitting in Reinforcement Learning

A major component of overfitting in model-free reinforcement learning (R...
12/06/2019 ∙ by Xingyou Song, et al. ∙ 21 ∙ share

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Semantic Photo Manipulation with a Generative Image Prior

Despite the recent success of GANs in synthesizing images conditioned on...
05/15/2020 ∙ by David Bau, et al. ∙ 21 ∙ share

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Theory of Minds: Understanding Behavior in Groups Through Inverse Planning

Human social behavior is structured by relationships. We form teams, gro...
01/18/2019 ∙ by Michael Shum, et al. ∙ 20 ∙ share

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EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Graph representation learning resurges as a trending research subject ow...
02/26/2019 ∙ by Aldo Pareja, et al. ∙ 20 ∙ share

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A Polynomial-time Solution for Robust Registration with Extreme Outlier Rates

We propose a robust approach for the registration of two sets of 3D poin...
03/20/2019 ∙ by Heng Yang, et al. ∙ 20 ∙ share

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Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization

We recover a video of the motion taking place in a hidden scene by obser...
12/05/2019 ∙ by Miika Aittala, et al. ∙ 20 ∙ share

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Overinterpretation reveals image classification model pathologies

Image classifiers are typically scored on their test set accuracy, but h...
03/19/2020 ∙ by Brandon Carter, et al. ∙ 20 ∙ share

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Subgraph Neural Networks

Deep learning methods for graphs achieve remarkable performance on many ...
06/18/2020 ∙ by Emily Alsentzer, et al. ∙ 20 ∙ share

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Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection

Semidefinite Programming (SDP) and Sums-of-Squares (SOS) relaxations hav...
09/18/2019 ∙ by Heng Yang, et al. ∙ 19 ∙ share

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Minimax Semiparametric Learning With Approximate Sparsity

Many objects of interest can be expressed as a linear, mean square conti...
12/27/2019 ∙ by Jelena Bradic, et al. ∙ 19 ∙ share

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What is the State of Neural Network Pruning?

Neural network pruning—the task of reducing the size of a network by rem...
03/06/2020 ∙ by Davis Blalock, et al. ∙ 19 ∙ share

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Efficiently testing local optimality and escaping saddles for ReLU networks

We provide a theoretical algorithm for checking local optimality and esc...
09/28/2018 ∙ by Chulhee Yun, et al. ∙ 18 ∙ share

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Predicting Factuality of Reporting and Bias of News Media Sources

We present a study on predicting the factuality of reporting and bias of...
10/02/2018 ∙ by Ramy Baly, et al. ∙ 18 ∙ share

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CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation

Infarcted brain tissue resulting from acute stroke readily shows up as h...
04/30/2019 ∙ by Jonathan Rubin, et al. ∙ 18 ∙ share

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A Study of Compositional Generalization in Neural Models

Compositional and relational learning is a hallmark of human intelligenc...
06/16/2020 ∙ by Tim Klinger, et al. ∙ 18 ∙ share

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Pareto-optimal data compression for binary classification tasks

The goal of lossy data compression is to reduce the storage cost of a da...
08/23/2019 ∙ by Max Tegmark, et al. ∙ 17 ∙ share

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Deep Context Map: Agent Trajectory Prediction using Location-specific Latent Maps

In this paper, we propose a novel approach for agent motion prediction i...
12/14/2019 ∙ by Igor Gilitschenski, et al. ∙ 17 ∙ share

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ARDA: Automatic Relational Data Augmentation for Machine Learning

Automatic machine learning () is a family of techniques to automate the ...
03/21/2020 ∙ by Nadiia Chepurko, et al. ∙ 17 ∙ share

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