🧠 AI Research - obaqueiro · Scour

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

💬LLMs Academic

Ultrafast machine learning on FPGAs via Kolmogorov-Arnold Networks

⚙️ML Engineering

aarushgupta.io··Lobsters, Hacker News

AI Paper Review: Training Language Models to Follow Instructions with Human Feedback (InstructGPT)

freecodecamp.org·

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

⚙️ML Engineering Blog

SLUUG Talk: Demystifying Large Language Models on Linux

💬LLMs Code

github.com··DEV

Backpropagation Without the Magic: A First-Principles Derivation

💬LLMs Blog

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The Emergence of Reproducibility and Generalizability in Diffusion Models

💬LLMs Academic

Flatland: The Adventures of Gradient Descent with Large Step Sizes

💬LLMs Academic

Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods

⚙️ML Engineering Academic

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

🧠Neuroscience Academic

Pseudospectral Bounds for Transient Amplification in Coupled Gradient Descent

⚙️ML Engineering Academic

Reinforcement Learning for Flow-Matching Policies with Density Transport

💬LLMs Academic

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

⚙️ML Engineering Academic

An Ensembled Latent Factor Model via Differential Evolution and Gradient Descent Optimization

💬LLMs Academic

Second-Order Path Kernel Interpolation Formulas in Machine Learning

⚙️ML Engineering Academic

Multilevel Stochastic Gradient Descent for Risk-Averse PDE-Constrained Optimization

🎓Computer Science Academic

Gradient Descent with Large Step Size Restores Symmetry in Deep Linear Networks with Multi-Pathway

⚙️ML Engineering Academic

Fourier fractal dimension to predict the generalization of deep neural networks

⚙️ML Engineering Academic

Large Language Models Should Learn Personalized Rather Than Aggregated Human Preferences

💬LLMs Academic

From Ticks to Flows: Dynamics of Neural Reinforcement Learning in Continuous Environments

🤖AI Academic

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