Signed pairwise interaction scores conflate U/R/S; Stochastic Hi-Fi uses interventional masked inference to recover per-feature uniqueness, redundancy, and synergy profiles.
Note on a Method for Calculating Corrected Sums of Squares and Products
9 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 9representative citing papers
Relativistic transport model for beta-particles in homologously expanding kilonova ejecta, incorporating per-species atomic data, shows non-local deposition and escape lower thermalization efficiency with analytic prescriptions supplied for light-curve codes.
A KDMC-based particle-level distribution decomposition for neutral transport with a Chapman-Enskog-derived fluid system, achieving ~500x speedup and ~10% L2 error versus full kinetic MC in 1D CX-dominant tests.
New cycle-consistent optimization, task vector theory, singular vector decompositions, adaptive routing, and efficient evolutionary search provide foundations for merging neural network weights across tasks.
Adaptive multi-criteria scoring with online logistic regression for Benders subproblem selection yields statistically significant runtime and integral improvements on 135 survivable network design instances.
EZR.py shows that a compact, readable Python toolkit can match or exceed state-of-the-art tools like SHAP, LIME, SMAC3, and FASTREAD on over 120 tabular SE tasks while running 500 times faster and using far less labeled data.
TOPPO reformulates PPO with critic balancing to address gradient ill-conditioning in multi-task RL and reports stronger mean and tail performance than SAC baselines on Meta-World+ using fewer parameters and steps.
An enhanced octree S^3 algorithm reduces CFD mesh cells 35-95% across three test cases while preserving dominant dynamics for efficient post-processing.
BluTrain is a native C++/CUDA training framework claiming 3% higher throughput and up to 22% lower memory use than PyTorch for 124M-parameter GPT-2 training on 8 GPUs while preserving numerical fidelity.
citing papers explorer
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The Representational Limit of Scalar Interactions: An Interventional Decomposition
Signed pairwise interaction scores conflate U/R/S; Stochastic Hi-Fi uses interventional masked inference to recover per-feature uniqueness, redundancy, and synergy profiles.
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Beta-Particle Transport and Thermalization in Kilonova Ejecta with Detailed Atomic Microphysics
Relativistic transport model for beta-particles in homologously expanding kilonova ejecta, incorporating per-species atomic data, shows non-local deposition and escape lower thermalization efficiency with analytic prescriptions supplied for light-curve codes.
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A kinetic-diffusion Monte Carlo-based particle-level fluid-kinetic decomposition for neutral transport simulations
A KDMC-based particle-level distribution decomposition for neutral transport with a Chapman-Enskog-derived fluid system, achieving ~500x speedup and ~10% L2 error versus full kinetic MC in 1D CX-dominant tests.
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Model Merging: Foundations and Algorithms
New cycle-consistent optimization, task vector theory, singular vector decompositions, adaptive routing, and efficient evolutionary search provide foundations for merging neural network weights across tasks.
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Adaptive Subproblem Selection in Benders Decomposition for Survivable Network Design Problems
Adaptive multi-criteria scoring with online logistic regression for Benders subproblem selection yields statistically significant runtime and integral improvements on 135 survivable network design instances.
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Can AI be Easy? Lessons Learned from the EZR.py Toolkit
EZR.py shows that a compact, readable Python toolkit can match or exceed state-of-the-art tools like SHAP, LIME, SMAC3, and FASTREAD on over 120 tabular SE tasks while running 500 times faster and using far less labeled data.
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TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing
TOPPO reformulates PPO with critic balancing to address gradient ill-conditioning in multi-task RL and reports stronger mean and tail performance than SAC baselines on Meta-World+ using fewer parameters and steps.
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An octree-based sampling algorithm for analyzing big simulation data
An enhanced octree S^3 algorithm reduces CFD mesh cells 35-95% across three test cases while preserving dominant dynamics for efficient post-processing.
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BluTrain: A C++/CUDA Framework for AI Systems
BluTrain is a native C++/CUDA training framework claiming 3% higher throughput and up to 22% lower memory use than PyTorch for 124M-parameter GPT-2 training on 8 GPUs while preserving numerical fidelity.