🤖 Machine Learning - tomasz

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

📈Data Science Code

github.com··Hacker News

A Theory on Flow Matching with Neural Networks

🧠Deep Learning Academic

arxiv.org·

Major Types of Machine Learning

💬Natural Language Processing Blog

medium.com·

Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential

🧠Deep Learning Academic

nature.com·

Day 45: Activation Functions and Loss Functions — Helping Neural Networks Learn Effectively

🧠Deep Learning Blog

medium.com

PyTorch Stochastic Gradient Optimization Technique

🧠Deep Learning

sitepoint.com·

Optimal Rates for Generalization of Gradient Descent Methods with Deep Neural Networks

🧠Deep Learning Academic

arxiv.org·

Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods

🧠Deep Learning Academic

arxiv.org·

meleantonio forked meleantonio/DEQN_Galo_03_2026 from sischei/DEQN_Galo_03_2026

🧠Deep Learning Code

github.com·

Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment

🧠Deep Learning Academic

arxiv.org·

Second-Order Path Kernel Interpolation Formulas in Machine Learning

🧠Deep Learning Academic

arxiv.org·

harshuljain13/llm-inference-at-scale: A Practitioner handbook for production llm serving.

💬Natural Language Processing Code

github.com··Hacker News

Verifiable and Confidential DNN Inference on Low-End Edge Devices

🧠Deep Learning Academic

arxiv.org·

Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods

🧠Deep Learning Academic

arxiv.org·

Predicting Physical and Physical-Chemical Properties of Molecular-Based Materials Using Computational Neural Networks

🧠Deep Learning Academic

arxiv.org·

Optimizing Energy-based Neural Network Training with Coherent Ising Machine

🧠Deep Learning Academic

arxiv.org·

Knockoffs-based False Discovery Rate Control and Simplification for Deep Neural Networks

🧠Deep Learning Academic

arxiv.org·

Statistically and Computationally Optimal Estimation and Inference of Common Subspaces

📈Data Science Academic

arxiv.org·

Welcome to Machine Learning With Manya: The Ultimate Adventure Map!

Model Evaluations: Prove Your Routing Policy Actually Works

ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.

A Theory on Flow Matching with Neural Networks

Major Types of Machine Learning

Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential

Day 45: Activation Functions and Loss Functions — Helping Neural Networks Learn Effectively

PyTorch Stochastic Gradient Optimization Technique

Optimal Rates for Generalization of Gradient Descent Methods with Deep Neural Networks

Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods

meleantonio forked meleantonio/DEQN_Galo_03_2026 from sischei/DEQN_Galo_03_2026

Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment

Second-Order Path Kernel Interpolation Formulas in Machine Learning

harshuljain13/llm-inference-at-scale: A Practitioner handbook for production llm serving.

Verifiable and Confidential DNN Inference on Low-End Edge Devices

Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods

Predicting Physical and Physical-Chemical Properties of Molecular-Based Materials Using Computational Neural Networks

Optimizing Energy-based Neural Network Training with Coherent Ising Machine

Knockoffs-based False Discovery Rate Control and Simplification for Deep Neural Networks

Statistically and Computationally Optimal Estimation and Inference of Common Subspaces