Stanisław Jastrzębski

DeepAI AI Chat

Featured Co-authors

Yoshua Bengio
438 publications
Kyunghyun Cho
210 publications
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201 publications
Aaron Courville
151 publications
Richard Socher
111 publications
Simon Lacoste-Julien
76 publications
Huan Wang
74 publications
Tomasz Trzciński
70 publications
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Pascal Vincent
56 publications
Amos Storkey
50 publications

research

∙ 10/16/2022

3D-GMIC: an efficient deep neural network to find small objects in large 3D images

3D imaging enables a more accurate diagnosis by providing spatial inform...

4 Jungkyu Park, et al. ∙

research

∙ 02/10/2022

Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks

We hypothesize that due to the greedy nature of learning in multi-modal ...

0 Nan Wu, et al. ∙

research

∙ 10/12/2021

Relative Molecule Self-Attention Transformer

Self-supervised learning holds promise to revolutionize molecule propert...

0 Łukasz Maziarka, et al. ∙

research

∙ 12/28/2020

Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization

The early phase of training has been shown to be important in two ways f...

16 Stanisław Jastrzębski, et al. ∙

research

∙ 11/28/2020

Differences between human and machine perception in medical diagnosis

Deep neural networks (DNNs) show promise in image-based medical diagnosi...

38 Taro Makino, et al. ∙

research

∙ 11/25/2020

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design

De novo molecule generation often results in chemically unfeasible molec...

0 Cheng-Hao Liu, et al. ∙

research

∙ 11/19/2020

Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks

Collider bias is a harmful form of sample selection bias that neural net...

5 Luke Darlow, et al. ∙

research

∙ 08/04/2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the COVID-19 pandemic, rapid and accurate triage of patients at t...

71 Farah E Shamout, et al. ∙

research

∙ 06/27/2020

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits

One of the key challenges in automated synthesis planning is to generate...

0 Mikołaj Sacha, et al. ∙

research

∙ 03/23/2020

Understanding the robustness of deep neural network classifiers for breast cancer screening

Deep neural networks (DNNs) show promise in breast cancer screening, but...

10 Witold Oleszkiewicz, et al. ∙

research

∙ 02/21/2020

The Break-Even Point on Optimization Trajectories of Deep Neural Networks

The early phase of training of deep neural networks is critical for thei...

18 Stanisław Jastrzębski, et al. ∙

research

∙ 02/19/2020

Molecule Attention Transformer

Designing a single neural network architecture that performs competitive...

0 Łukasz Maziarka, et al. ∙

research

∙ 06/11/2019

Large Scale Structure of Neural Network Loss Landscapes

There are many surprising and perhaps counter-intuitive properties of op...

0 Stanislav Fort, et al. ∙

research

∙ 04/06/2019

Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift

Recent work has shown that using unlabeled data in semi-supervised learn...

0 Michał Zając, et al. ∙

research

∙ 03/20/2019

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

We present a deep convolutional neural network for breast cancer screeni...

3 Nan Wu, et al. ∙

research

∙ 03/01/2019

Non-linear ICA based on Cramer-Wold metric

Non-linear source separation is a challenging open problem with many app...

0 Przemysław Spurek, et al. ∙

research

∙ 02/02/2019

Parameter-Efficient Transfer Learning for NLP

Fine-tuning large pre-trained models is an effective transfer mechanism ...

0 Neil Houlsby, et al. ∙

research

∙ 12/27/2018

Neural Architecture Search Over a Graph Search Space

Neural architecture search (NAS) enabled the discovery of state-of-the-a...

0 Quentin de Laroussilhe, et al. ∙

research

∙ 09/24/2018

Dynamical Isometry is Achieved in Residual Networks in a Universal Way for any Activation Function

We demonstrate that in residual neural networks (ResNets) dynamical isom...

0 Wojciech Tarnowski, et al. ∙

research

∙ 07/13/2018

DNN's Sharpest Directions Along the SGD Trajectory

Recent work has identified that using a high learning rate or a small ba...

4 Stanisław Jastrzębski, et al. ∙

research

∙ 05/23/2018

Cramer-Wold AutoEncoder

We propose a new generative model, Cramer-Wold Autoencoder (CWAE). Follo...

0 Jacek Tabor, et al. ∙

research

∙ 04/24/2018

Commonsense mining as knowledge base completion? A study on the impact of novelty

Commonsense knowledge bases such as ConceptNet represent knowledge in th...

0 Stanisław Jastrzębski, et al. ∙

research

∙ 11/13/2017

Three Factors Influencing Minima in SGD

We study the properties of the endpoint of stochastic gradient descent (...

0 Stanisław Jastrzębski, et al. ∙

research

∙ 10/13/2017

Residual Connections Encourage Iterative Inference

Residual networks (Resnets) have become a prominent architecture in deep...

0 Stanisław Jastrzębski, et al. ∙

research

∙ 06/16/2017

A Closer Look at Memorization in Deep Networks

We examine the role of memorization in deep learning, drawing connection...

0 Devansh Arpit, et al. ∙

research

∙ 06/01/2017

Learning to Compute Word Embeddings On the Fly

Words in natural language follow a Zipfian distribution whereby some wor...

0 Dzmitry Bahdanau, et al. ∙

research

∙ 02/07/2017

How to evaluate word embeddings? On importance of data efficiency and simple supervised tasks

Maybe the single most important goal of representation learning is makin...

0 Stanisław Jastrzębski, et al. ∙

research

∙ 02/19/2016

Learning to SMILE(S)

This paper shows how one can directly apply natural language processing ...

0 Stanisław Jastrzębski, et al. ∙