🔄 Meta-Learning - inarcissuss · Scour

👨‍💻Karpathy arXiv·

Kalman Prototypical Networks for Few-shot Fault Detection in Combined Cycle Gas Turbines

🔍Interpretability biorxiv.org·

Few-Shot Classification of C. elegans Developmental Stages via Explainable Hierarchical Hyperbolic Graph Embeddings

🤖AI/ML medium.com

·

How Siamese Networks Learn Similarity: Contrastive, Triplet, ArcFace, and Circle Loss Explained

🤖人工智能 Nature·

Predicting the strength of waste aggregate concrete blocks using novel hybrid machine learning models and graphical user interface deployment

🤖AI/ML journals.plos.org·

pyhgf: A neural network library for predictive coding

🤖人工智能 people.idsia.ch·

Munich 1991: The Roots of the Current AI Boom

Covers 2 stories including DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Discussed on Hacker News and Lobsters

🔀LoRA arXiv·

Exploring Dualistic Meta-Learning to Enhance Domain Generalization in Open Set Scenarios

🤖Machine Learning arXiv·

Learning Dynamical Systems from Multiple Sparse Datasets: A Hierarchical Bayesian Modeling Approach

🤖人工智能 arXiv·

A welding penetration prediction model for laser welding process based on self-supervised learning using physics-informed neural networks

🔬ML Research arXiv·

Reconstructing Randomly Masked Spectra Helps DNNs Identify Discriminant Wavenumbers

🧠LLM Research arXiv·

Adaptive Hebbian Memory Routing in Vision Transformers for Few-Shot Learning

🎮Reinforcement Learning arXiv·

Learning to Adapt: Reptile-D-Learning for Robust and Efficient Control Under Parametric Uncertainty

⚡Transformers arXiv·

Neural Operator Processes for Probabilistic Operator Learning under Partial Observations

⚡LLM Optimization arXiv·

Constrained Variable Projection for Structured Problems

🎮Reinforcement Learning arXiv·

Meta-Reinforcement Learning via Evolution for Multi-Objective Combinatorial Supply Chain Optimisation

Log in to enable infinite scrolling