Media Summary: Original Paper: "Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks" Find the paper at: ... NIPS 2018: Unsupervised Learning of View-invariant Action Representations 3-minute video for the paper "Learning Task Specifications from Demonstrations" (

Nips 2018 A Simple Unified - Detailed Analysis & Overview

Original Paper: "Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks" Find the paper at: ... NIPS 2018: Unsupervised Learning of View-invariant Action Representations 3-minute video for the paper "Learning Task Specifications from Demonstrations" ( This video describes the paper "Improving We present an unsupervised approach for learning to estimate three dimensional (3D) facial structure from a single image while ... Tutorial Deep Learning: Practice and Trends. Nando de Freitas, Scott Reed, Oriol Vinyals. 0:02:06 Part I: Practice. The Deep ...

This is a short presentation for the paper "Sparsified SGD with Memory". Sebastian U. Stich, Jean-Baptiste Cordonnier, Martin ... See and Think: Disentangling Semantic Scene Completion (NIPS 2018) Constantinos Daskalakis, Nishanth Dikkala and Siddhartha Jayanti.

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NIPS 2018 - A simple unified framework for detecting out-of-distribution and adversarial attacks
Sparsity in CNNs NeurIPS (NIPS) 2018 (1 min presentation)
NIPS 2018: Unsupervised Learning of View-invariant Action Representations
NIPS 2018 HIGHLIGHT
[NIPS/NeurIPS 2018] Learning Task Specifications from Demonstrations
Improving Simple Models with Confidence Profiles NIPS 2018
DepthNets (NIPS 2018)
Deep Learning: Practice and Trends (NIPS 2017 Tutorial, parts I & II)
NIPS 2018
[NIPS/NeurIPS 2018] Sparsified SGD with Memory
FP8 Training @NeurIPS 2018 (NIPS2018)
See and Think: Disentangling Semantic Scene Completion (NIPS 2018)
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NIPS 2018 - A simple unified framework for detecting out-of-distribution and adversarial attacks

NIPS 2018 - A simple unified framework for detecting out-of-distribution and adversarial attacks

3 min overview of

Sparsity in CNNs NeurIPS (NIPS) 2018 (1 min presentation)

Sparsity in CNNs NeurIPS (NIPS) 2018 (1 min presentation)

Original Paper: "Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks" Find the paper at: ...

NIPS 2018: Unsupervised Learning of View-invariant Action Representations

NIPS 2018: Unsupervised Learning of View-invariant Action Representations

NIPS 2018: Unsupervised Learning of View-invariant Action Representations

NIPS 2018 HIGHLIGHT

NIPS 2018 HIGHLIGHT

The video highlight of the

[NIPS/NeurIPS 2018] Learning Task Specifications from Demonstrations

[NIPS/NeurIPS 2018] Learning Task Specifications from Demonstrations

3-minute video for the paper "Learning Task Specifications from Demonstrations" (

Improving Simple Models with Confidence Profiles NIPS 2018

Improving Simple Models with Confidence Profiles NIPS 2018

This video describes the paper "Improving

DepthNets (NIPS 2018)

DepthNets (NIPS 2018)

We present an unsupervised approach for learning to estimate three dimensional (3D) facial structure from a single image while ...

Deep Learning: Practice and Trends (NIPS 2017 Tutorial, parts I & II)

Deep Learning: Practice and Trends (NIPS 2017 Tutorial, parts I & II)

Tutorial Deep Learning: Practice and Trends. Nando de Freitas, Scott Reed, Oriol Vinyals. 0:02:06 Part I: Practice. The Deep ...

NIPS 2018

NIPS 2018

NIPS 2018

[NIPS/NeurIPS 2018] Sparsified SGD with Memory

[NIPS/NeurIPS 2018] Sparsified SGD with Memory

This is a short presentation for the paper "Sparsified SGD with Memory". Sebastian U. Stich, Jean-Baptiste Cordonnier, Martin ...

FP8 Training @NeurIPS 2018 (NIPS2018)

FP8 Training @NeurIPS 2018 (NIPS2018)

This video is for NeurIPS

See and Think: Disentangling Semantic Scene Completion (NIPS 2018)

See and Think: Disentangling Semantic Scene Completion (NIPS 2018)

See and Think: Disentangling Semantic Scene Completion (NIPS 2018)

NIPS 2018: HOGWILD!-Gibbs Can be Pan-Accurate

NIPS 2018: HOGWILD!-Gibbs Can be Pan-Accurate

Constantinos Daskalakis, Nishanth Dikkala and Siddhartha Jayanti.