Pieter-Jan Kindermans | DeepAI

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∙ 08/22/2023

StoryBench: A Multifaceted Benchmark for Continuous Story Visualization

Generating video stories from text prompts is a complex task. In additio...

0 Emanuele Bugliarello, et al. ∙

∙ 10/05/2022

Phenaki: Variable Length Video Generation From Open Domain Textual Description

We present Phenaki, a model capable of realistic video synthesis, given ...

11 Ruben Villegas, et al. ∙

∙ 04/25/2022

When adversarial examples are excusable

Neural networks work remarkably well in practice and theoretically they ...

0 Pieter-Jan Kindermans, et al. ∙

∙ 04/15/2022

Resource-Constrained Neural Architecture Search on Tabular Datasets

The best neural architecture for a given machine learning problem depend...

0 Chengrun Yang, et al. ∙

∙ 08/18/2020

Discovering Multi-Hardware Mobile Models via Architecture Search

Developing efficient models for mobile phones or other on-device deploym...

0 Grace Chu, et al. ∙

∙ 08/13/2020

Can weight sharing outperform random architecture search? An investigation with TuNAS

Efficient Neural Architecture Search methods based on weight sharing hav...

15 Gabriel Bender, et al. ∙

∙ 04/30/2020

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

Inverted bottleneck layers, which are built upon depthwise convolutions,...

15 Yunyang Xiong, et al. ∙

∙ 03/24/2020

BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models

Neural architecture search (NAS) has shown promising results discovering...

6 Jiahui Yu, et al. ∙

∙ 12/02/2019

Neural Predictor for Neural Architecture Search

Neural Architecture Search methods are effective but often use complex a...

0 Wei Wen, et al. ∙

∙ 08/13/2018

iNNvestigate neural networks!

In recent years, deep neural networks have revolutionized many applicati...

0 Maximilian Alber, et al. ∙

∙ 08/08/2018

Backprop Evolution

The back-propagation algorithm is the cornerstone of deep learning. Desp...

4 Maximilian Alber, et al. ∙

∙ 06/28/2018

Evaluating Feature Importance Estimates

Estimating the influence of a given feature to a model prediction is cha...

4 Sara Hooker, et al. ∙

∙ 11/02/2017

The (Un)reliability of saliency methods

Saliency methods aim to explain the predictions of deep neural networks....

0 Pieter-Jan Kindermans, et al. ∙

∙ 11/01/2017

Don't Decay the Learning Rate, Increase the Batch Size

It is common practice to decay the learning rate. Here we show one can u...

0 Samuel L. Smith, et al. ∙

∙ 06/26/2017

SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Deep learning has the potential to revolutionize quantum chemistry as it...

0 Kristof T. Schütt, et al. ∙

∙ 05/16/2017

Learning how to explain neural networks: PatternNet and PatternAttribution

DeConvNet, Guided BackProp, LRP, were invented to better understand deep...

0 Pieter-Jan Kindermans, et al. ∙

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