13 citations · 13 across the 1 of their papers we have counts for
5 papers
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling
Hannes Eriksson, Christos Dimitrakakis, Lars Carlsson
We study the problem of performing automated experiment design for drug screening through Bayesian inference and optimisation. In particular, we compare and contrast the behaviour…
Retrain or not retrain: Conformal test martingales for change-point detection
Vladimir Vovk, Ivan Petej, Ilia Nouretdinov +3
We argue for supplementing the process of training a prediction algorithm by setting up a scheme for detecting the moment when the distribution of the data changes and the algorith…
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets
Ola Spjuth, Robin Carrión Brännström, Lars Carlsson +1
Conformal Prediction is a framework that produces prediction intervals based on the output from a machine learning algorithm. In this paper we explore the case when training data i…
Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction
Ola Spjuth, Lars Carlsson, Niharika Gauraha
Conformal Prediction is a machine learning methodology that produces valid prediction regions under mild conditions. In this paper, we explore the application of making predictions…
Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery
Niharika Gauraha, Lars Carlsson, Ola Spjuth
This paper explores conformal prediction in the learning under privileged information (LUPI) paradigm. We use the SVM+ realization of LUPI in an inductive conformal predictor, and…