2 citations · 3 across the 4 of their papers we have counts for
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cs.LG2026
Calibrating Scientific Foundation Models with Inference-Time Stochastic Attention
Akash Yadav, Taiwo A. Adebiyi, Ruda Zhang
Transformer-based scientific foundation models are increasingly deployed in high-stakes settings, but current architectures give deterministic outputs and provide limited support f…
cs.LG2025
Bayesian Optimization under Uncertainty for Training a Scale Parameter in Stochastic Models
Akash Yadav, Ruda Zhang
Hyperparameter tuning is a challenging problem especially when the system itself involves uncertainty. Due to noisy function evaluations, optimization under uncertainty can be comp…
cs.LG2025★ 1 cited
Differential Machine Learning for Time Series Prediction
Akash Yadav, Eulalia Nualart
Accurate time series prediction is challenging due to the inherent nonlinearity and sensitivity to initial conditions. We propose a novel approach that enhances neural network pred…