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Scoured 18 posts in 5.4 ms

Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field deformation data

 🧠Deep Learning  Content type: Academic
arxiv.org·
Less-relevant results

Machine learning from scratch, what to build before using scikit-learn

 🕸️Neural Networks  Content type: Tutorial
iwtlp.com··DEV

A primer on automatic differentiation (2015)

 ⚙️Model Training  Content type: PDF

princezuda/-RequiemGPT-: Fully open source and open weights built and trained by fable five with one prompt. An experience in how AI actually works

 🛠️ML Frameworks  Content type: Code
github.com··Hacker News

Mutual Information Optimization via K-Recursion and Automatic Differentiation for Linear Gaussian Wireless Networks

 🕸️Neural Networks  Content type: Academic
arxiv.org·

Apple WWDC On-Device AI Deep Dive - Google Docs

 🤖Machine Learning
gist.is··Hacker News

Training-Inference Kernel Contracts: Bounding Divergence in Post-Training and Deployment

 🛠️ML Frameworks  Content type: Academic
arxiv.org·

Why JAX Is a Much Better Backend for Quantum Circuit Simulation Than PyTorch

 🛠️ML Frameworks  Content type: Code
github.com
··DEV

Adaptive directional gradients for parameterised quantum circuits

 🤖Machine Learning  Content type: Academic
arxiv.org·

Compile Once, Differentiate Everywhere: A Differentiable Meta-Circular Interpreter

 🔥Burn  Content type: Academic
arxiv.org·

Database as a Graph for Relational Deep Learning

 🧠Deep Learning

I stopped using most of Rust’s advanced features for my ML library

 🛠️ML Frameworks  Content type: Code
github.com··r/rust

On the conditional equivalence of phase retrieval algorithms

 🤖Machine Learning  Content type: Academic
arxiv.org·

Magenta RealTime 2: Open and Local Live Music Models

 ML Inference

Constraint-driven Optimization and Parametrization of Industrial NURBS Geometries via Neural Deformation Field

 🗜️Quantization  Content type: Academic
arxiv.org·

Liesel: A Python Framework for Graph-Based Bayesian Modeling and Customizable MCMC with Support for Generalized Additive Models

 🛠️ML Frameworks  Content type: Academic
arxiv.org·

jdalang/jda-lang: Jda: A high-performance systems language bootstrapped from assembly. Beats C on sudoku & LZ77. Self-hosted compiler, no GC, built-in concurrency & ML.

 🦀Rust  Content type: Code
github.com··DEV

Full-Field Calibration of Coupled Thermomechanical Material Models at Finite Strain

 🔄MLOps  Content type: Academic
arxiv.org·

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