activity
20112026
most citedMonte Carlo Methods for Tempo Tracking and Rhythm Quantization

98 citations · 379 across the 33 of their papers we have counts for

collaborators

33 papers

cs.AI2026

Towards Conversational Medical AI with Eyes, Ears and a Voice

Meet Shah, Jason Gusdorf, Anil Palepu +50

The practice of medicine relies not only upon skillful dialogue but also on the nuanced exchange and interpretation of rich auditory and visual cues between doctors and patients. B…

cs.LG2024★ 2 cited

Mitigating LLM Hallucinations via Conformal Abstention

Yasin Abbasi Yadkori, Ilja Kuzborskij, David Stutz +9

We develop a principled procedure for determining when a large language model (LLM) should abstain from responding (e.g., by saying "I don't know") in a general domain, instead of…

cs.LG2023★ 1 cited

Conformal prediction under ambiguous ground truth

David Stutz, Abhijit Guha Roy, Tatiana Matejovicova +3

Conformal Prediction (CP) allows to perform rigorous uncertainty quantification by constructing a prediction set satisfying for a user-chose…

cs.LG2023★ 2 cited

Evaluating AI systems under uncertain ground truth: a case study in dermatology

David Stutz, Ali Taylan Cemgil, Abhijit Guha Roy +17

For safety, medical AI systems undergo thorough evaluations before deployment, validating their predictions against a ground truth which is assumed to be fixed and certain. However…

cs.CV2023★ 15 cited

Generative models improve fairness of medical classifiers under distribution shifts

Ira Ktena, Olivia Wiles, Isabela Albuquerque +9

A ubiquitous challenge in machine learning is the problem of domain generalisation. This can exacerbate bias against groups or labels that are underrepresented in the datasets used…

cs.LG2023★ 2 cited

Transformers Meet Directed Graphs

Simon Geisler, Yujia Li, Daniel Mankowitz +3

Transformers were originally proposed as a sequence-to-sequence model for text but have become vital for a wide range of modalities, including images, audio, video, and undirected…