/dev/posts/ Home Tags Archives Vulnerabilities Code Configuration Neural Network Distillation Published: Jan 30 2025 Updated: Jan 30 2025 Comment Share Like Dislike Other reaction Previous episode: Transformer-decoder language models Overview of neural network distillation as done in “Distilling the Knowledge in a Neural Network” (Hinton et al, 2014). Table of content Primary objective Secondary objective Explanations Overview What? Transferring knowledge from one classifier neural network f^* (the

Spiking Neural Network (SNN) is considered more biologically realistic and power-efficient as it imitates the fundamental mechanism of the human brain. Recently, backpropagation (BP) based SNN learning algorithms that utilize deep learning frameworks have achieved good performance. However, bio-interpretability is partially neglected in those BP-based algorithms. Toward bio-plausible BP-based SNNs, we consider three properties in modeling spike activities: Multiplicity, Adaptability, and Plasticity (MAP). I

Spiking Neural Networks As Universal Function Approximators

Discover Generative Adversarial Networks (GANs), their types, applications, training process, and practical implementation in this guide

Abstract page for arXiv paper 1807.06699: Adaptive Neural Trees

Over the past two decades. network science has developed statistical methods to analyze and model patterns in complex networks. Similarly, the deep learning community has recently developed new approaches to generalize neural network architectures to graph-structured data. Unfortunately, there are few interactions between these two communities. In a new preprint, we highlight challenges of opportunites at the intersection between network science and deep graph learning

Funtamental Machine Learning principles and concepts that are extended into Deep Neural Networks

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A new study reveals the neural dynamics of consciousness. Using AI and advanced imaging in mice, scientists have identified a "conscious variable" and the metastable patterns that define the awake brain

田中専務 拓海先生、最近部下が「直交行列を使うとRNNが安定する」って言ってきまして、正直ピンと来ないんです。…