🧠 Deep Learning - tomasz · Scour

Artificial Neural Networks (ANNs) and Deep Learning Foundations 🤖Machine Learning

·3d

MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes 👁️Computer Vision

MegaTrain Full Precision Training of 100B+ Parameter LLMs on a Single GPU 🤖Local LLMs

github.com·1d·Hacker News

A novel deep learning architecture for multi-source data fusion 👁️Computer Vision

techxplore.com·3d

Hardware, GPUs, and Distributed Training: AI Infrastructure Explained 💬Prompt Engineering

·3d

Shipping Your Image Classification Model With Confidence 🤖Machine Learning

mlops.community·5d

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations 🏗️System Design

(VBS-NN) ML – 512k context length pre-training on a 12GB GPU 🥶Cold Start Problem

github.com·1d·Hacker News

When and Why Adversarial Training Improves PINNs: A Neural Tangent Kernel Perspective 🤖Machine Learning

A Few GPUs, A Whole Lotta Scale: Faithful LLM Training Emulation with PrismLLM 🤖Local LLMs

d2l-ai/d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. 🔍Vector Search

Efficient and provably convergent end-to-end training of deep neural networks with linear constraints 🔍Vector Search

A Transfer Learning Evaluation of Deep Neural Networks for Image Classification 🤖Machine Learning

Freeze Deep, Train Shallow: Interpretable Layer Allocation for Continued Pre-Training 🤖Machine Learning

Deep Learning for Solving and Estimating Dynamic Models in Economics and Finance 🤖Machine Learning

Brain Tumor Classification in MRI Images: A Computationally Efficient Convolutional Neural Network 👁️Computer Vision

One-Step Generative Modeling via Wasserstein Gradient Flows 🔢Kolmogorov Complexity

Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation 🤖Machine Learning

Training-Inference Consistent Segmented Execution for Long-Context LLMs 🧠LLM Reasoning

LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models 🧠LLM Reasoning

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