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Design of potent antimalarials with generative chemistry
Recent advances in generative modelling allow designing novel compounds through deep
neural networks. One such neural network model, JT-VAE (the Junction Tree Variational …
neural networks. One such neural network model, JT-VAE (the Junction Tree Variational …
Feature space saturation during training
We propose layer saturation-a simple, online-computable method for analyzing the
information processing in neural networks. First, we show that a layer's output can be …
information processing in neural networks. First, we show that a layer's output can be …
Complexity for deep neural networks and other characteristics of deep feature representations
RA Janik, P Witaszczyk - arxiv preprint arxiv:2006.04791, 2020 - arxiv.org
We define a notion of complexity, which quantifies the nonlinearity of the computation of a
neural network, as well as a complementary measure of the effective dimension of feature …
neural network, as well as a complementary measure of the effective dimension of feature …
[PDF][PDF] Delve: Neural Network Feature Variance Analysis
Designing neural networks is a complex task. Deep neural networks are often referred to as
“black box” models-little insight in the function they approximate is gained from looking at the …
“black box” models-little insight in the function they approximate is gained from looking at the …
Exploring the properties and evolution of neural network eigenspaces during training
We investigate properties and the evolution of the emergent inference process inside neural
networks using layer saturation [1] and logistic regression probes [2]. We demonstrate that …
networks using layer saturation [1] and logistic regression probes [2]. We demonstrate that …
Analyzing the Inference Process in Deep Convolutional Neural Networks using Principal Eigenfeatures, Saturation and Logistic Regression Probes
The predictive performance of a neural network depends on the one hand on the difficulty of
a problem, defined by the number of classes and complexity of the visual domain, and on …
a problem, defined by the number of classes and complexity of the visual domain, and on …
Investigating the Learning Progress of CNNs in Script Identification Using Gradient Values
Demands for an automatic translation based on Camera-based Multilingual Optical
Character Recognition (CM-OCR) are increasing. In addition, CM-OCR methods usually …
Character Recognition (CM-OCR) are increasing. In addition, CM-OCR methods usually …
[PDF][PDF] CNN を用いた言語判定における学習過程の分析
冨岡永伍 - mie-u.repo.nii.ac.jp
社会の国際化に伴い, カメラベース OCR を用いた自動翻訳ソフトウェアの需要が高まっている.
撮影した画像から多言語の文字を同時に直接認識するカメラベース OCR の実現は困難であるため …
撮影した画像から多言語の文字を同時に直接認識するカメラベース OCR の実現は困難であるため …
[CYTOWANIE][C] TOWARDS GUIDED NEURAL ARCHITECTURE DESIGN BY SPECTRAL ANALYSIS
ML Richter, J Shenk - 2019