MIT

∙ Cambridge , United States ∙ 0 followers

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

Featured Researchers

Yu Zhang
124 publications
Ruslan Salakhutdinov
106 publications
Hao Wang
95 publications
Anima Anandkumar
78 publications
Yue Wang
74 publications
James Glass
74 publications
Jie Chen
73 publications
Joshua B. Tenenbaum
66 publications
Antonio Torralba
65 publications
Zheng Zhang
63 publications
Pin-Yu Chen
58 publications

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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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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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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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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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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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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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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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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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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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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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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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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Every Local Minimum is a Global Minimum of an Induced Model

For non-convex optimization in machine learning, this paper proves that ...
04/07/2019 ∙ by Kenji Kawaguchi, et al. ∙ 16 ∙ share

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The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development

As machine learning is applied more and more widely, data scientists oft...
05/22/2019 ∙ by Micah J. Smith, et al. ∙ 16 ∙ share

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Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

In classification applications, we often want probabilistic predictions ...
06/23/2019 ∙ by Zhilu Zhang, et al. ∙ 16 ∙ share

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Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

We introduce a new video synthesis task: synthesizing time lapse videos ...
01/04/2020 ∙ by Amy Zhao, et al. ∙ 16 ∙ share

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kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion

Manipulation planning is the task of computing robot trajectories that m...
09/16/2019 ∙ by Wei Gao, et al. ∙ 15 ∙ share

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ℓ_∞ Vector Contraction for Rademacher Complexity

We show that the Rademacher complexity of any R^K-valued function class ...
11/15/2019 ∙ by Dylan J. Foster, et al. ∙ 15 ∙ share

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Reasoning About Physical Interactions with Object-Oriented Prediction and Planning

Object-based factorizations provide a useful level of abstraction for in...
12/28/2018 ∙ by Michael Janner, et al. ∙ 14 ∙ share

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Learning protein sequence embeddings using information from structure

Inferring the structural properties of a protein from its amino acid seq...
02/22/2019 ∙ by Tristan Bepler, et al. ∙ 14 ∙ share

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Kernel Instrumental Variable Regression

Instrumental variable regression is a strategy for learning causal relat...
06/01/2019 ∙ by Rahul Singh, et al. ∙ 14 ∙ share

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Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias

Supporting model interpretability for complex phenomena where annotators...
09/20/2019 ∙ by Asma Ghandeharioun, et al. ∙ 14 ∙ share

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Deep Evidential Regression

Deterministic neural networks (NNs) are increasingly being deployed in s...
10/07/2019 ∙ by Alexander Amini, et al. ∙ 14 ∙ share

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Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Classical deformable registration techniques achieve impressive results ...
03/08/2019 ∙ by Adrian V. Dalca, et al. ∙ 13 ∙ share

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Learning to guide task and motion planning using score-space representation

In this paper, we propose a learning algorithm that speeds up the search...
07/26/2018 ∙ by Beomjoon Kim, et al. ∙ 12 ∙ share

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Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

The prediction accuracy has been the long-lasting and sole standard for ...
08/05/2018 ∙ by Dong Su, et al. ∙ 12 ∙ share

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How Powerful are Graph Neural Networks?

Graph Neural Networks (GNNs) for representation learning of graphs broad...
10/01/2018 ∙ by Keyulu Xu, et al. ∙ 12 ∙ share

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Finite sample expressive power of small-width ReLU networks

We study universal finite sample expressivity of neural networks, define...
10/17/2018 ∙ by Chulhee Yun, et al. ∙ 12 ∙ share

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SGD without Replacement: Sharper Rates for General Smooth Convex Functions

We study stochastic gradient descent without replacement () for smooth ...
03/04/2019 ∙ by Prateek Jain, et al. ∙ 12 ∙ share

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Unsupervised Discovery of Parts, Structure, and Dynamics

Humans easily recognize object parts and their hierarchical structure by...
03/12/2019 ∙ by Zhenjia Xu, et al. ∙ 12 ∙ share

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