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Roman Vaculin

3 accepted papers

2026

Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring.

ICLR 2026poster

We propose a post-hoc adaptive conformal anomaly detection method for monitoring time series that leverages predictions from pre-trained foundation models without requiring additional fine-tuning. Our method yields an interpretable anomaly score directly interpretable as a false alarm rate (p-value)…

Cited by 0SourcecodeScholar
2024

Identifying Homogeneous and Interpretable Groups for Conformal Prediction

UAI 2024poster

Conformal prediction methods are a tool for uncertainty quantification of a model’s prediction, providing a model-agnostic and distribution-free statistical wrapper that generates prediction intervals/sets for a given model with finite sample generalization guarantees. However, these guarantees hol…

Cited by 2SourcePDFScholar
2019

Differentially Private Distributed Data Summarization under Covariate Shift

NeurIPS 2019poster

We envision Artificial Intelligence marketplaces to be platforms where consumers, with very less data for a target task, can obtain a relevant model by accessing many private data sources with vast number of data samples. One of the key challenges is to construct a training dataset that matches a t…

Cited by 8SourcePDFScholar