Results for “neural-networks”
19 skills
jiachen-t-wang multimodal-neurons-in-artificial-neural-networks-arxiv-2103-
Multimodal Neurons in Artificial Neural Networks
6
k-dense-ai deepchem
Predict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
30.2k · bundle
bouclem deep-learning
PyTorch, TensorFlow, neural networks, CNNs, transformers, and deep learning for production
7 · bundle
More results
nous-hermeshub yann-lecun
Agente que simula Yann LeCun — inventor das Convolutional Neural Networks, Chief AI Scientist da Meta, Prêmio Turing 2018.
1
jiachen-t-wang scaling-laws-for-neural-language-models-arxiv-2001-08361v1
Scaling Laws for Neural Language Models
6
jiachen-t-wang emu-generative-pretraining-in-multimodality-arxiv-2307-05222
Emu: Generative Pretraining in Multimodality
6
dotnet technology-selection
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI, Microsoft Agent Framework, GitHub Copilot SDK, ONNX Runtime, and OllamaSharp.
4k
tinh2 game-ai
Analyzes game AI systems in a codebase, covering behavior trees, finite state machines, GOAP, utility AI, pathfinding, steering, perception, difficulty adaptation, NPC dialogue, and AI debugging tools for Unity, Unreal, and Godot projects.
13
mukul975 hunting-for-unusual-network-connections
Hunt for unusual network connections by analyzing outbound traffic patterns, rare destinations, non-standard ports, and anomalous connection frequencies from endpoints.
24.6k · bundle
jiachen-t-wang nlvr2-a-visual-reasoning-benchmark-for-natural-language-arxi
NLVR2: A Visual Reasoning Benchmark for Natural Language
6
curiositech alphago-deep-rl
Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system
10 · bundle
jiachen-t-wang towards-open-world-segmentation-of-parts-arxiv-2305-06914v3
Towards Open-World Segmentation of Parts
6
intense-visions perf-n-plus-one
N+1 Query Detection and Resolution
18 · bundle
jiachen-t-wang autoaugment-learning-augmentation-strategies-from-data-arxiv
AutoAugment: Learning Augmentation Strategies from Data
6
snoodleboot-io ensemble-methods
Expected error decomposes into bias, variance, and irreducible noise.
2
ssrjkk pytorch
Builds and trains deep learning models with PyTorch, including tensors, autograd, and neural network modules.
2 · bundle
orchestra-research sparse-autoencoder-training
Train and analyze Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features for mechanistic interpretability research.
10.4k · bundle
smith6jt-cop pytorch-common-pitfalls
Fixes common PyTorch bugs including percentile calculations, LayerNorm for Conv1d, and buffer edge cases in reinforcement learning and neural network code.
3
k-dense-ai pytorch-lightning
Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard, MLflow), and distributed training (DDP, FSDP, DeepSpeed) for scalable neural network training.
30.2k · bundle