Dmitry Efimov — accepted AI-conference papers

2026

Probabilistic Pretraining for Improved Neural Regression

Boris Oreshkin, Shiv Tavker, Dmitry Efimov

ICML 2026poster

While transfer learning has revolutionized computer vision and natural language processing, its application to probabilistic regression remains underexplored, particularly for tabular data. We introduce NIAQUE (Neural Interpretable Any-Quantile Estimation), a novel permutation-invariant architecture…

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2026

Zero-shot Forecasting by Simulation Alone

Boris N. Oreshkin, Mayank Jauhari, Ravi Kiran Selvam, Malcolm Wolff, Shankar Ramasubramanian, Kin G. Olivares +7

ICLR 2026poster

Zero-shot time-series forecasting holds great promise, but is still in its infancy, hindered by limited and biased data corpora, leakage-prone evaluation, and privacy and licensing constraints. We propose the first practical univariate time-series simulation pipeline, which is simultaneously fast en…

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