Soumith Chintala | DeepAI

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∙ 09/21/2023

See to Touch: Learning Tactile Dexterity through Visual Incentives

Equipping multi-fingered robots with tactile sensing is crucial for achi...

0 Irmak Güzey, et al. ∙

∙ 03/21/2023

Dexterity from Touch: Self-Supervised Pre-Training of Tactile Representations with Robotic Play

Teaching dexterity to multi-fingered robots has been a longstanding chal...

0 Irmak Güzey, et al. ∙

∙ 12/02/2022

Navigating to Objects in the Real World

Semantic navigation is necessary to deploy mobile robots in uncontrolled...

0 Théophile Gervet, et al. ∙

∙ 10/12/2022

Holo-Dex: Teaching Dexterity with Immersive Mixed Reality

A fundamental challenge in teaching robots is to provide an effective in...

9 Sridhar Pandian Arunachalam, et al. ∙

∙ 10/11/2022

CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory

We propose CLIP-Fields, an implicit scene model that can be trained with...

0 Nur Muhammad Mahi Shafiullah, et al. ∙

∙ 10/28/2021

TorchAudio: Building Blocks for Audio and Speech Processing

This document describes version 0.10 of torchaudio: building blocks for ...

0 Yao-Yuan Yang, et al. ∙

∙ 06/28/2020

PyTorch Distributed: Experiences on Accelerating Data Parallel Training

This paper presents the design, implementation, and evaluation of the Py...

0 Shen Li, et al. ∙

∙ 12/03/2019

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Deep learning frameworks have often focused on either usability or speed...

90 Adam Paszke, et al. ∙

∙ 10/03/2019

Generalized Inner Loop Meta-Learning

Many (but not all) approaches self-qualifying as "meta-learning" in deep...

12 Edward Grefenstette, et al. ∙

∙ 02/15/2017

Training Language Models Using Target-Propagation

While Truncated Back-Propagation through Time (BPTT) is the most popular...

0 Sam Wiseman, et al. ∙

∙ 01/29/2017

Transformation-Based Models of Video Sequences

In this work we propose a simple unsupervised approach for next frame pr...

0 Joost van Amersfoort, et al. ∙

∙ 01/26/2017

Wasserstein GAN

We introduce a new algorithm named WGAN, an alternative to traditional G...

0 Martin Arjovsky, et al. ∙

∙ 11/25/2016

Semantic Segmentation using Adversarial Networks

Adversarial training has been shown to produce state of the art results ...

0 Pauline Luc, et al. ∙

∙ 11/01/2016

TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games

We present TorchCraft, a library that enables deep learning research on ...

0 Gabriel Synnaeve, et al. ∙

∙ 09/10/2016

Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks

We consider scenarios from the real-time strategy game StarCraft as new ...

0 Nicolas Usunier, et al. ∙

∙ 05/26/2016

Discovering Causal Signals in Images

This paper establishes the existence of observable footprints that revea...

0 David Lopez-Paz, et al. ∙

∙ 04/07/2016

A MultiPath Network for Object Detection

The recent COCO object detection dataset presents several new challenges...

0 Sergey Zagoruyko, et al. ∙

∙ 11/23/2015

MazeBase: A Sandbox for Learning from Games

This paper introduces MazeBase: an environment for simple 2D games, desi...

0 Sainbayar Sukhbaatar, et al. ∙

∙ 06/26/2015

Convolutional networks and learning invariant to homogeneous multiplicative scalings

The conventional classification schemes -- notably multinomial logistic ...

0 Mark Tygert, et al. ∙

∙ 06/18/2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

In this paper we introduce a generative parametric model capable of prod...

0 Emily Denton, et al. ∙

∙ 03/11/2015

A mathematical motivation for complex-valued convolutional networks

A complex-valued convolutional network (convnet) implements the repeated...

0 Joan Bruna, et al. ∙

∙ 12/24/2014

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

We examine the performance profile of Convolutional Neural Network train...

0 Nicolas Vasilache, et al. ∙

∙ 12/01/2012

Pedestrian Detection with Unsupervised Multi-Stage Feature Learning

Pedestrian detection is a problem of considerable practical interest. Ad...

0 Pierre Sermanet, et al. ∙

∙ 04/18/2012

Convolutional Neural Networks Applied to House Numbers Digit Classification

We classify digits of real-world house numbers using convolutional neura...

0 Pierre Sermanet, et al. ∙

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