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Machine Learning

Training an AI to play Resident Evil Requiem using Behavior Cloning + HG-DAgge [P]

Code of Project: https://github.com/paulo101977/notebooks-rl/tree/main/re_requiem I’ve been working on training an agent to play a segmen...

Reddit - Machine Learning · 1 min ·
Machine Learning

Educational PyTorch repo for distributed training from scratch: DP, FSDP, TP, FSDP+TP, and PP [P]

I put together a small educational repo that implements distributed training parallelism from scratch in PyTorch: https://github.com/shre...

Reddit - Machine Learning · 1 min ·
UMKC Announces New Master of Science in Artificial Intelligence
Ai Infrastructure

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

AI News - General · 4 min ·

All Content

[2511.16148] Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models
Machine Learning

[2511.16148] Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models

Abstract page for arXiv paper 2511.16148: Enhancing Nuclear Reactor Core Simulation through Data-Based Surrogate Models

arXiv - Machine Learning · 3 min ·
[2601.16399] A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning
Llms

[2601.16399] A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to LLM Fine-Tuning

Abstract page for arXiv paper 2601.16399: A Hessian-Free Actor-Critic Algorithm for Bi-Level Reinforcement Learning with Applications to ...

arXiv - Machine Learning · 4 min ·
[2601.00473] Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning
Machine Learning

[2601.00473] Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning

Abstract page for arXiv paper 2601.00473: Deep Neural Networks as Discrete Dynamical Systems: Implications for Physics-Informed Learning

arXiv - Machine Learning · 4 min ·
[2511.18789] Perturbing the Derivative: Doubly Wild Refitting for Model-Free Evaluation of Opaque Machine Learning Predictors
Machine Learning

[2511.18789] Perturbing the Derivative: Doubly Wild Refitting for Model-Free Evaluation of Opaque Machine Learning Predictors

Abstract page for arXiv paper 2511.18789: Perturbing the Derivative: Doubly Wild Refitting for Model-Free Evaluation of Opaque Machine Le...

arXiv - Machine Learning · 4 min ·
[2511.18000] Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Individual Behavioral Learning
Machine Learning

[2511.18000] Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Individual Behavioral Learning

Abstract page for arXiv paper 2511.18000: Reward Engineering for Spatial Epidemic Simulations: A Reinforcement Learning Platform for Indi...

arXiv - Machine Learning · 4 min ·
[2512.03923] Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations
Machine Learning

[2512.03923] Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

Abstract page for arXiv paper 2512.03923: Quantum-Classical Physics-Informed Neural Networks for Solving Reservoir Seepage Equations

arXiv - Machine Learning · 4 min ·
[2511.18178] Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability
Machine Learning

[2511.18178] Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability

Abstract page for arXiv paper 2511.18178: Bayesian Calibration of Engine-out NOx Models for Engine-to-Engine Transferability

arXiv - Machine Learning · 4 min ·
[2511.11743] Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts
Machine Learning

[2511.11743] Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

Abstract page for arXiv paper 2511.11743: Uncertainty Makes It Stable: Curiosity-Driven Quantized Mixture-of-Experts

arXiv - Machine Learning · 4 min ·
[2511.06767] QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations
Machine Learning

[2511.06767] QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common Patterns in Nonlinear Operations

Abstract page for arXiv paper 2511.06767: QUARK: Quantization-Enabled Circuit Sharing for Transformer Acceleration by Exploiting Common P...

arXiv - Machine Learning · 4 min ·
[2510.27321] MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electrocardiogram Data
Machine Learning

[2510.27321] MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electrocardiogram Data

Abstract page for arXiv paper 2510.27321: MedM2T: A MultiModal Framework for Time-Aware Modeling with Electronic Health Record and Electr...

arXiv - Machine Learning · 4 min ·
[2510.14814] Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift
Machine Learning

[2510.14814] Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

Abstract page for arXiv paper 2510.14814: Tackling Time-Series Forecasting Generalization via Mitigating Concept Drift

arXiv - Machine Learning · 4 min ·
[2510.15495] OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning
Machine Learning

[2510.15495] OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

Abstract page for arXiv paper 2510.15495: OffSim: Offline Simulator for Model-based Offline Inverse Reinforcement Learning

arXiv - Machine Learning · 4 min ·
[2510.14751] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries
Llms

[2510.14751] Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

Abstract page for arXiv paper 2510.14751: Beyond Multi-Token Prediction: Pretraining LLMs with Future Summaries

arXiv - Machine Learning · 3 min ·
[2510.06020] RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics
Machine Learning

[2510.06020] RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

Abstract page for arXiv paper 2510.06020: RamPINN: Recovering Raman Spectra From Coherent Anti-Stokes Spectra Using Embedded Physics

arXiv - Machine Learning · 4 min ·
[2510.00430] PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment
Machine Learning

[2510.00430] PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

Abstract page for arXiv paper 2510.00430: PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment

arXiv - Machine Learning · 4 min ·
[2510.01169] Fiaingen: A financial time series generative method matching real-world data quality
Machine Learning

[2510.01169] Fiaingen: A financial time series generative method matching real-world data quality

Abstract page for arXiv paper 2510.01169: Fiaingen: A financial time series generative method matching real-world data quality

arXiv - Machine Learning · 4 min ·
[2509.24140] A signal separation view of classification
Machine Learning

[2509.24140] A signal separation view of classification

Abstract page for arXiv paper 2509.24140: A signal separation view of classification

arXiv - Machine Learning · 3 min ·
[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning
Machine Learning

[2508.17381] DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

Abstract page for arXiv paper 2508.17381: DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning

arXiv - Machine Learning · 3 min ·
[2508.02330] A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps
Machine Learning

[2508.02330] A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

Abstract page for arXiv paper 2508.02330: A Compression Based Classification Framework Using Symbolic Dynamics of Chaotic Maps

arXiv - Machine Learning · 4 min ·
[2507.21037] When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding
Llms

[2507.21037] When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject Motor Imagery Decoding

Abstract page for arXiv paper 2507.21037: When Brain Foundation Model Meets Cauchy-Schwarz Divergence: A New Framework for Cross-Subject ...

arXiv - Machine Learning · 4 min ·
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