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, alongside 661 external citations. Polarity classification is still indexing.
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representative citing papers
Beta particles from r-process decay heat and ionize kilonova ejecta non-locally, so transport and detailed atomic data change the predicted temperature and ionization state.
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.
A native C++/CUDA training framework matches PyTorch numerics on 124M GPT-2 while reporting ~3% higher throughput and up to 22% lower VRAM on 8× RTX 6000 Ada.
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 octree-based rewrite of the Sparse Spatial Sampling algorithm reduces CFD snapshot data by 35–98% while preserving dominant POD modes in the two validated benchmark cases.
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
Beta particles from r-process decay heat and ionize kilonova ejecta non-locally, so transport and detailed atomic data change the predicted temperature and ionization state.
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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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BluTrain: A C++/CUDA Framework for AI Systems
A native C++/CUDA training framework matches PyTorch numerics on 124M GPT-2 while reporting ~3% higher throughput and up to 22% lower VRAM on 8× RTX 6000 Ada.
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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.
-
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 octree-based rewrite of the Sparse Spatial Sampling algorithm reduces CFD snapshot data by 35–98% while preserving dominant POD modes in the two validated benchmark cases.