ABC: Adaptive BayesNet Structure Learning for Computational Scalable Multi-task Image Compression
arxiv.orgยท1d
๐Ÿง Learned Compression
Can All Knowledge Be Mined? A Formal Framework for ฯ†^โˆž Consequence Closure
researchgate.netยท15hยท
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๐Ÿ”ขDenotational Semantics
10 Must-Know Python Libraries for MLOps in 2025
machinelearningmastery.comยท22h
๐Ÿ”„Archive Workflows
QTIP: Quantization with Trellises and Incoherence Processing
arxiv.orgยท1d
๐Ÿ“ŠVector Quantization
Unfolding the Future: Understanding Recurrent Neural Networks
dev.toยท6hยท
Discuss: DEV
๐ŸŒŠStream Processing
MITโ€™s Optical AI Chip That Could Revolutionize 6G at the Speed of Light
scitechdaily.comยท4h
๐Ÿ”ฌOptical Physics
Benchmarking Neural Network Training Algorithms
arxiv.orgยท1d
๐Ÿง Machine Learning
Enhancing Vector Quantization with Distributional Matching: A Theoretical and Empirical Study
arxiv.orgยท1d
๐Ÿ“ŠVector Quantization
Unsupervised pretraining in biological neural networks
nature.comยท1d
๐Ÿง Machine Learning
Energy Costs of Communicating with AI
frontiersin.orgยท9hยท
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๐Ÿ’ปLocal LLMs
MLA: K/V cache compression with low-rank projection
huggingface.coยท2dยท
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๐Ÿ“ŠVector Quantization
A Unified Multimodal Approach to Speech Processing with LLMs
hackernoon.comยท21h
๐Ÿ—ฃ๏ธCMU Pronouncing
The Gumbel-Softmax Distribution
sassafras13.github.ioยท1dยท
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๐Ÿง Machine Learning
Structured Output for Beginners and 3 Prompting Tips
pocketflow.substack.comยท7hยท
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๐ŸŒณIncremental Parsing
Interpretability and Generalization Bounds for Learning Spatial Physics
arxiv.orgยท1d
๐Ÿง Machine Learning
Lambda : History-Aware Bayesian Jump Event Detector for Time Series (with Dual EYE Mode)
dev.toยท8hยท
Discuss: DEV
๐ŸงฌBitstream Evolution
Dynamic ASR Pathways: An Adaptive Masking Approach Towards Efficient Pruning of A Multilingual ASR Model
arxiv.orgยท1d
๐ŸŒŠStreaming Compression
Show HN: DeepThink Plugin โ€“ Bring Gemini 2.5's parallel reasoning to open models
news.ycombinator.comยท1dยท
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๐ŸงฎSMT Solvers
Time-dependent density estimation using binary classifiers
arxiv.orgยท1d
๐Ÿง Machine Learning
Predicting Onflow Parameters Using Transfer Learning for Domain and Task Adaptation
arxiv.orgยท1d
๐Ÿ“ŠLearned Metrics