Summary of Scaling and Renormalization in High-dimensional Regression, by Alexander Atanasov et al.
Scaling and renormalization in high-dimensional regressionby Alexander Atanasov, Jacob A. Zavatone-Veth, Cengiz PehlevanFirst submitted to…
Scaling and renormalization in high-dimensional regressionby Alexander Atanasov, Jacob A. Zavatone-Veth, Cengiz PehlevanFirst submitted to…
A Careful Examination of Large Language Model Performance on Grade School Arithmeticby Hugh Zhang, Jeff…
Neural Controlled Differential Equations with Quantum Hidden Evolutionsby Lingyi Yang, Zhen ShaoFirst submitted to arxiv…
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networksby Yunzhen Feng, Tim G. J.…
MAP-Former: Multi-Agent-Pair Gaussian Joint Predictionby Marlon Steiner, Marvin Klemp, Christoph StillerFirst submitted to arxiv on:…
On Improving the Algorithm-, Model-, and Data- Efficiency of Self-Supervised Learningby Yun-Hao Cao, Jianxin WuFirst…
Revisiting Multi-modal Emotion Learning with Broad State Space Models and Probability-guidance Fusionby Yuntao Shou, Tao…
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect Estimationby Yoichi Chikahara, Kansei UshiyamaFirst submitted to…
MD-NOMAD: Mixture density nonlinear manifold decoder for emulating stochastic differential equations and uncertainty propagationby Akshay…
Private Optimal Inventory Policy Learning for Feature-based Newsvendor with Unknown Demandby Tuoyi Zhao, Wen-xin Zhou,…