Real-time stock volatility prediction with deep learning on a time-series DB
⚡ONNX Runtime
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Low-Level Hacks
📊Profiling Tools
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Variational Data-Consistent Assimilation
arxiv.org·3h
🎓Model Distillation
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MeixnerNet: Adaptive and Robust Spectral Graph Neural Networks with Discrete Orthogonal Polynomials
arxiv.org·3h
🔀Operator Fusion
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MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
arxiv.org·3h
📊Gradient Accumulation
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Isotropic Curvature Model for Understanding Deep Learning Optimization: Is Gradient Orthogonalization Optimal?
arxiv.org·3h
📉Model Quantization
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MobileNetV3 Paper Walkthrough: The Tiny Giant Getting Even Smarter
towardsdatascience.com·1d
🎯Tensor Cores
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Phased DMD: Few-step Distribution Matching Distillation via Score Matching within Subintervals
arxiv.org·1d
🧮cuDNN
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The Infrastructure of Modern Ran king Systems, Part 2: The Data Layer - Fueling the Models with Feature and Vector Stores
shaped.ai·1d
⚡ONNX Runtime
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A filtering scheme for confocal laser endomicroscopy (CLE)-video sequences for self-supervised learning
arxiv.org·3h
🧮cuDNN
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Spatial Secrets: Unleashing Language Models with Unexpected Masking by Arvind Sundararajan
📉Model Quantization
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MaGNet: A Mamba Dual-Hypergraph Network for Stock Prediction via Temporal-Causal and Global Relational Learning
arxiv.org·3h
⚡ONNX Runtime
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From Uniform to Adaptive: General Skip-Block Mechanisms for Efficient PDE Neural Operators
arxiv.org·3h
🏎️TensorRT
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OSMGen: Highly Controllable Satellite Image Synthesis using OpenStreetMap Data
arxiv.org·3h
🏎️TensorRT
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pDANSE: Particle-based Data-driven Nonlinear State Estimation from Nonlinear Measurements
arxiv.org·1d
🔄ONNX
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A generative adversarial network optimization method for damage detection and digital twinning by deep AI fault learning: Z24 Bridge structural health monitorin...
arxiv.org·3h
🧮cuDNN
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Gated DeltaNet (Linear Attention variant in Qwen3-Next and Kimi Linear)
👁️Attention Optimization
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Bayesian Natural Gradient Fine-Tuning of CLIP Models via Kalman Filtering
arxiv.org·3h
📊Gradient Accumulation
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