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[2604.01345] Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
Ai Infrastructure

[2604.01345] Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning

Abstract page for arXiv paper 2604.01345: Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning

arXiv - Machine Learning · 3 min ·
[2604.01342] Massively Parallel Exact Inference for Hawkes Processes
Machine Learning

[2604.01342] Massively Parallel Exact Inference for Hawkes Processes

Abstract page for arXiv paper 2604.01342: Massively Parallel Exact Inference for Hawkes Processes

arXiv - Machine Learning · 3 min ·
[2604.01337] SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
Machine Learning

[2604.01337] SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving

Abstract page for arXiv paper 2604.01337: SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving

arXiv - Machine Learning · 3 min ·
[2604.01329] Model Merging via Data-Free Covariance Estimation
Machine Learning

[2604.01329] Model Merging via Data-Free Covariance Estimation

Abstract page for arXiv paper 2604.01329: Model Merging via Data-Free Covariance Estimation

arXiv - Machine Learning · 3 min ·
[2604.01315] Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling
Machine Learning

[2604.01315] Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling

Abstract page for arXiv paper 2604.01315: Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling

arXiv - Machine Learning · 4 min ·
[2604.01328] Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial
Machine Learning

[2604.01328] Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial

Abstract page for arXiv paper 2604.01328: Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial

arXiv - Machine Learning · 3 min ·
[2604.01313] JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics
Machine Learning

[2604.01313] JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics

Abstract page for arXiv paper 2604.01313: JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics

arXiv - Machine Learning · 4 min ·
[2604.01308] An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis
Machine Learning

[2604.01308] An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis

Abstract page for arXiv paper 2604.01308: An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Lim...

arXiv - Machine Learning · 4 min ·
[2604.01305] UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression

[2604.01305] UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression

Abstract page for arXiv paper 2604.01305: UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing v...

arXiv - Machine Learning · 4 min ·
[2604.01298] Forecasting Supply Chain Disruptions with Foresight Learning
Llms

[2604.01298] Forecasting Supply Chain Disruptions with Foresight Learning

Abstract page for arXiv paper 2604.01298: Forecasting Supply Chain Disruptions with Foresight Learning

arXiv - Machine Learning · 3 min ·
[2604.01279] Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method
Machine Learning

[2604.01279] Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method

Abstract page for arXiv paper 2604.01279: Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method

arXiv - Machine Learning · 4 min ·
[2604.01261] DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting
Machine Learning

[2604.01261] DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting

Abstract page for arXiv paper 2604.01261: DySCo: Dynamic Semantic Compression for Effective Long-term Time Series Forecasting

arXiv - Machine Learning · 3 min ·

Perplexity's "Incognito Mode" is a "sham," lawsuit says

submitted by /u/Gloomy_Nebula_5138 [link] [comments]

Reddit - Artificial Intelligence · 1 min ·

Built an AI “project brain” to run and manage engineering projects solo, how can I make this more efficient?

Recently, I built something I call a “project brain” using Google AI Studio. It helps me manage end to end operations for engineering pro...

Reddit - Artificial Intelligence · 1 min ·

I just noticed something

Pattern Recognition, Gatekeeping, and the Myth of “We Can Always Tell” A Comparative Analysis of Anti-AI Sentiment and Transphobic Rhetor...

Reddit - Artificial Intelligence · 1 min ·

Ai the Real Risk

Everyone is asking: “Can AI solve this?” AI can verify anything that’s structured and repeatable. But that’s not where the real risk is. ...

Reddit - Artificial Intelligence · 1 min ·
Llms

"Oops! ChatGPT is Temporarily Unavailable!": A Diary Study on Knowledge Workers' Experiences of LLM Withdrawal

submitted by /u/Special-Steel [link] [comments]

Reddit - Artificial Intelligence · 1 min ·
Generative Ai

OpenAI is throwing away Sora’s real value

If the issue with Sora is compute cost, then shutting down the entire platform — including Sora 1 — doesn’t make much sense. Sora 1’s ima...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

[D] Physicist-turned-ML-engineer looking to get into ML research. What's worth working on and where can I contribute most?

After years of focus on building products, I'm carving out time to do independent research again and trying to find the right direction. ...

Reddit - Machine Learning · 1 min ·
95% of faculty say AI making students dangerously dependent on technology for learning: survey

95% of faculty say AI making students dangerously dependent on technology for learning: survey

A new survey finds 95% of faculty worry artificial intelligence makes students overly reliant on AI, with 90% saying it decreases critica...

AI News - General · 7 min ·