Fredrik Johansson

Associate Professor at Data Science and AI

Source: chalmers.se
Image of Fredrik Johansson

Showing 44 publications

2023

Sharing Pattern Submodels for Prediction with Missing Values

Lena Stempfle, Ashkan Panahi, Fredrik Johansson
Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023. Vol. 37, p. 9882-9890
Paper in proceeding
2023

Using Satellite Images and Deep Learning to Measure Health and Living Standards in India

Adel Daoud, Felipe Jordán, Makkunda Sharma et al
Social Indicators Research. Vol. 167 (1-3), p. 475-505
Journal article
2023

Assessing clusters of comorbidities in rheumatoid arthritis: a machine learning approach

Daniel H. Solomon, Hongshu Guan, Fredrik Johansson et al
Arthritis Research and Therapy. Vol. 25 (1)
Journal article
2023

Image-based Treatment Effect Heterogeneity

Connor T. Jerzak, Fredrik Johansson, Adel Daoud
Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022. Vol. 213, p. 531-552
Paper in proceeding
2023

Time Series of Satellite Imagery Improve Deep Learning Estimates of Neighborhood-Level Poverty in Africa

Markus Pettersson, Mohammad Kakooei, Julia Ortheden et al
IJCAI International Joint Conference on Artificial Intelligence. Vol. 2023-August, p. 6165-6173
Paper in proceeding
2022

Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models

Rickard K. A. Karlsson, Martin Willbo, Zeshan Hussain et al
Proceedings of Machine Learning Research. Vol. 151, p. 5459-5484
Paper in proceeding
2022

ADCB: An Alzheimer's disease simulator for benchmarking observational estimators of causal effects

Newton Mwai Kinyanjui, Fredrik Johansson
Conference on Health, Inference, and Learning. Vol. 2022
Paper in proceeding
2022

ADCB: An Alzheimer’s disease simulator for benchmarking observational estimators of causal effects

Newton Mwai Kinyanjui, Fredrik Johansson
Proceedings of Machine Learning Research. Vol. 174, p. 103-118
Paper in proceeding
2022

Practicality of generalization guarantees for unsupervised domain adaptation with neural networks

Adam Breitholtz, Fredrik Johansson
Transactions on Machine Learning Research. Vol. 10
Journal article
2022

Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects

Fredrik Johansson, U. Shalit, Nathan Kallus et al
Journal of Machine Learning Research. Vol. 23 (166), p. 1-50
Journal article
2022

Efficient learning of nonlinear prediction models with time-series privileged information

Bastian Jung, Fredrik Johansson
Advances in Neural Information Processing Systems. Vol. 35
Paper in proceeding
2022

Case-Based Off-Policy Evaluation Using Prototype Learning

Anton Matsson, Fredrik Johansson
Proceedings of Machine Learning Research. Vol. 180, p. 1339-1349
Paper in proceeding
2021

Thompson Sampling for Bandits with Clustered Arms

Emil Carlsson, Devdatt Dubhashi, Fredrik Johansson
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Paper in proceeding
2021

Predicting response to tocilizumab monotherapy in rheumatoid arthritis: A real-world data analysis using machine learning

Fredrik Johansson, Jamie Collins, Vincent Yau et al
Journal of Rheumatology. Vol. 48 (9), p. 1364-1370
Journal article
2021

The sequence of disease-modifying anti-rheumatic drugs: pathways to and predictors of tocilizumab monotherapy

Daniel H. Solomon, Chang Xu, Jamie Collins et al
Arthritis Research and Therapy. Vol. 23 (1)
Journal article
2021

Learning Approximate and Exact Numeral Systems via Reinforcement Learning

Emil Carlsson, Devdatt Dubhashi, Fredrik Johansson
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021. Vol. 43
Paper in proceeding
2021

Predicting progression and cognitive decline in amyloid-positive patients with Alzheimer’s disease

Hákon Valur Dansson, Lena Stempfle, Hildur Egilsdóttir et al
Alzheimers Research and Therapy. Vol. 13 (1)
Journal article
2020

Learning to search efficiently for causally near-optimal treatments

Samuel Håkansson, Viktor Lindblom, Omer Gottesman et al
Advances in Neural Information Processing Systems. Vol. 2020-December
Paper in proceeding
2020

Characterization of Overlap in Observational Studies

Michael Oberst, Fredrik Johansson, Dennis Wei et al
Proceedings of Machine Learning Research. Vol. 108, p. 788-797
Paper in proceeding
2020

Estimation of bounds on potential outcomes for decision making

Maggie Makar, Fredrik Johansson, John Guttag et al
37th International Conference on Machine Learning, ICML 2020. Vol. PartF168147-9, p. 6617-6627
Paper in proceeding
2020

Predicting Remission Among Patients With Rheumatoid Arthritis Starting Tocilizumab Monotherapy: Model Derivation and Remission Score Development

Jamie Collins, Fredrik Johansson, Sara Gale et al
ACR open rheumatology. Vol. 2 (2), p. 65-73
Journal article
2020

A survey on graph kernels

Nils M. Kriege, Fredrik Johansson, Christopher Morris
Applied Network Science. Vol. 5 (1)
Review article
2020

Support and Invertibility in Domain-Invariant Representations

Fredrik Johansson, Rajesh Ranganath, David Sontag
AISTATS 2019- 22nd International Conference in Artificial Intelligence and Statistics
Paper in proceeding
2020

Estimation of Utility-Maximizing Bounds on Potential Outcomes

Maggie Makar, Fredrik Johansson, John Guttag et al
Proceedings of the 37th International Conference on Machine Learning. Vol. 119
Paper in proceeding
2019

Guidelines for reinforcement learning in healthcare

Omer Gottesman, Fredrik Johansson, Matthieu Komorowski et al
Nature Medicine. Vol. 25 (1), p. 16-18
Other text in scientific journal
2018

Why is my classifier discriminatory?

Irene Chen, Fredrik Johansson, David Sontag
Proceedings of the 32nd International Conference on Neural Information Processing Systems. Vol. 32, p. 3543-3554
Paper in proceeding
2017

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery

Ashkan Panahi, Devdatt Dubhashi, Fredrik Johansson et al
Proceedings of Machine Learning Research. Vol. 6, p. 4247-4260
Paper in proceeding
2017

Estimating individual treatment effect: generalization bounds and algorithms

U. Shalit, Fredrik Johansson, David Sontag
Proceedings of the 34th International Conference on Machine Learning . Vol. 6, p. 4709-4718
Paper in proceeding
2016

Learning with Geometric Embeddings of Graphs

Fredrik Johansson
Doctoral thesis
2016

Learning representations for counterfactual inference

Fredrik Johansson, U. Shalit, D. Sontag
33rd International Conference on Machine Learning, ICML 2016, New York City, United States; 19 June 2016 through 24 June 2016, p. 4407-4418
Paper in proceeding
2015

Classifying large graphs with differential privacy

Fredrik Johansson, Otto Frost, Carl Thufvesson Retzner et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9321, p. 3-7
Paper in proceeding
2015

Visions and open challenges for a knowledge-based culturomics

Nina Tahmasebi, Lars Borin, Gabriele Capannini et al
International Journal on Digital Libraries. Vol. 15 (2-4), p. 169-187
Journal article
2015

Generalized shortest path kernel on graphs

L. Hermansson, Fredrik Johansson, O. Watanabe
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9356, p. 78-85
Paper in proceeding
2015

Neural context embeddings for automatic discovery of word senses

Mikael Kågebäck, Fredrik Johansson, Richard Johansson et al
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing. Denver, United States, p. 25-32
Paper in proceeding
2015

Weighted theta functions and embeddings with applications to Max-Cut, clustering and summarization

Fredrik Johansson, A. Chattoraj, C. Bhattacharyya et al
Advances in Neural Information Processing Systems. Vol. 2015-January, p. 1018-1026
Paper in proceeding
2015

Learning with similarity functions on graphs using matchings of geometric embeddings

Fredrik Johansson, Devdatt Dubhashi
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Vol. 2015-August, p. 467-476
Paper in proceeding
2014

Global graph kernels using geometric embeddings

Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi et al
Proceedings of the 31st International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, p. 694-702
Paper in proceeding
2014

Global geometric graph kernels and applications

Fredrik Johansson
Licentiate thesis
2013

DLOREAN: Dynamic Location-aware Reconstruction of multiway Networks

Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi
2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013; Dallas, TX; United States; 7 December 2013 through 10 December 2013, p. 1012-1019
Paper in proceeding
2013

Entity disambiguation in anonymized graphs using graph kernels

Linus Hermansson, Tommi Kerola, Fredrik Johansson et al
22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 27 October 2013 through 1 November 2013, p. 1037-1046
Paper in proceeding
2012

Intent-aware temporal query modeling for keyword suggestion

Fredrik Johansson, Tobias Färdig, Vinay Jethava et al
International Conference on Information and Knowledge Management, Proceedings, p. 83-86
Paper in proceeding

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Showing 9 research projects

2023–2026

Causality and auxiliary information for efficient machine learning

Fredrik Johansson Data Science and AI 1
Swedish Research Council (VR)

2020–2021

AI and Missingness in Diagnostics for Alzheimer’s Disease

Fredrik Johansson Data Science
Chalmers AI Research Centre

2020–2024

Machine Learning for Causal Inference from Observational Data with Applications in Healthcare

Fredrik Johansson Data Science
Wallenberg AI, Autonomous Systems and Software Program

2 publications exist
2020–2025

Foundations for Learning Transferable Concepts

Fredrik Johansson Data Science
Wallenberg AI, Autonomous Systems and Software Program

3 publications exist
2020–2020

Yata – Intelligent systems to improve and support education

Simon Pettersson Fors Subatomic, High Energy and Plasma Physics
Christian Forssén Subatomic, High Energy and Plasma Physics
Devdatt Dubhashi Data Science
Fredrik Johansson Data Science
Dag Wedelin Data Science
Chalmers AI Research Centre (CHAIR)
Chalmers

2020–2022

Poverty traps in Africa

Fredrik Johansson Data Science
Formas

2019–

Deep Reinforcement Learning: Principles and Applications in Cognitive Science and Networks (

Devdatt Dubhashi Data Science
Fredrik Johansson Data Science
Chalmers AI Research Centre (CHAIR)

2019–2023

WASP AI/MLX Professorship

Fredrik Johansson Data Science
Wallenberg AI, Autonomous Systems and Software Program

6 publications exist
2012–2016

Data-Driven Secure Business Intelligence (DataBIN)

David Sands Software Technology (Chalmers)
Devdatt Dubhashi Computing Science (Chalmers)
Peter Damaschke Computing Science (Chalmers)
Gerardo Schneider Software Technology (Chalmers)
Olof Mogren Computing Science (Chalmers)
Raul Pardo Jimenez Software Technology (Chalmers)
Hamid Ebadi Tavallaei Software Technology (Chalmers)
Fredrik Johansson Computing Science (Chalmers)
Andrei Sabelfeld Software Technology (Chalmers)
Swedish Foundation for Strategic Research (SSF)

There might be more projects where Fredrik Johansson participates, but you have to be logged in as a Chalmers employee to see them.