Physics Priors Offer Useful Accuracy-Carbon Trade-Offs in Spatio-Temporal Forecasting - 惯性聚合

推荐订阅源

博客园 - Franky

Proofpoint News Feed

Palo Alto Networks Blog

Hackread – Cybersecurity News, Data Breaches, AI and More

The Register - Security

Security @ Cisco Blogs

Simon Willison's Weblog

Recorded Future

大猫的无限游戏

Microsoft Research Blog - Microsoft Research

Tailwind CSS Blog

cs.CV updates on arXiv.org

Cyber Security Advisories - MS-ISAC

Application and Cybersecurity Blog

True Tiger Recordings

有赞技术团队

Cisco Talos Blog

Hacker News - Newest: "LLM"

The GitHub Blog

cs.AI updates on arXiv.org

博客园 - 叶小钗

Hugging Face - Blog

Hacker News: Ask HN

Security Archives - TechRepublic

Future of Privacy Forum

PCI Perspectives

Help Net Security

让小产品的独立变现更简单 - ezindie.com

The Blog of Author Tim Ferriss

Netflix TechBlog - Medium

罗磊的独立博客

Apple Machine Learning Research

Security Latest

美团技术团队

博客园 - 三生石上(FineUI控件)

Schneier on Security

CERT Recently Published Vulnerability Notes

cs.LG updates on arXiv.org

Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation When to Switch, Not Just What: Transition Quality Prediction in Clash Royale Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation Provable Joint Decontamination for Benchmarking Multiple Large Language Models Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling Dynamic Mixture of Latent Memories for Self-Evolving Agents Aerodynamic force reconstruction using physics-informed Gaussian processes MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Scaling of Diffusion Language Models Cross-domain benchmarks reveal when coordinated AI agents improve scientific inference from partial evidence Bandit Convex Optimization with Gradient Prediction Adaptivity Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes CausalGuard: Conformal Inference under Graph Uncertainty OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity Temporal Contrastive Transformer for Financial Crime Detection: Self-Supervised Sequence Embeddings via Predictive Contrastive Coding LCGuard: Latent Communication Guard for Safe KV Sharing in Multi-Agent Systems How Many Different Outputs Can a Transformer Generate? Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization Double descent for least-squares interpolation on contaminated data: A simulation study ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction AgForce Enables Antigen-conditioned Generative Antibody Design On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability Support-aware offline policy selection for advertising marketplaces Can Transformers Learn to Verify During Backtracking Search? EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series Detecting Atypical Clients in Federated Learning via Representation-Level Divergence Evaluation of Pipelines for Data Integration into Knowledge Graphs Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs What are the Right Symmetries for Formal Theorem Proving? MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking Harnesses for Inference-Time Alignment over Execution Trajectories Skill Weaving: Efficient LLM Improvement via Modular Skillpacks $\textit{BlockFormer}$ : Transformer-based inference from interaction maps Machine learning prediction of obstructive coronary artery disease using opportunistic coronary calcium and epicardial fat assessments from CT calcium scoring scans Predicting Performance of Symbolic and Prompt Programs with Examples When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning Tabular foundation models for robust calibration of near-infrared chemical sensing data Three Costs of Amortizing Gaussian Process Inference with Neural Processes Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction Calibration, Uncertainty Communication, and Deployment Readiness in CKD Risk Prediction: A Framework Evaluation Study Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics Same Architecture, Different Capacity: Optimizer-Induced Spectral Scaling Laws Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale How Sparsity Allocation Shapes Label-Free Post-Pruning Recoverability ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data One-Way Policy Optimization for Self-Evolving LLMs Toward Understanding Adversarial Distillation: Why Robust Teachers Fail Thermodynamic Irreversibility of Training Algorithms LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition Manifold-Guided Attention Steering TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems Noise Schedule Design for Diffusion Models: An Optimal Control Perspective Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies Alike Parts: A Feature-Informed Approach to Local and Global Prototype Explanations Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification Symbolic Density Estimation for Discrete Distributions

Physics Priors Offer Useful Accuracy-Carbon Trade-Offs in Spatio-Temporal Forecasting

Sophia N. Wi · 2026-05-23 · via cs.LG updates on arXiv.org

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。原文来自 — 版权归原作者所有。