| Software Framework for Data Fault Injection to Test Machine Learning Systems JK Nurminen, T Halvari, J Harviainen, J Mylläri, A Röyskö, J Silvennoinen, ... 2019 IEEE International Symposium on Software Reliability Engineering …, 2019 | 13 | 2019 |
| On inference and learning with probabilistic generating circuits J Harviainen, VP Ramaswamy, M Koivisto Uncertainty in Artificial Intelligence, 829-838, 2023 | 7 | 2023 |
| Approximating the Permanent with Deep Rejection Sampling J Harviainen, A Röyskö, M Koivisto Advances in Neural Information Processing Systems 34, 213-224, 2021 | 6 | 2021 |
| Revisiting Bayesian network learning with small vertex cover J Harviainen, M Koivisto Uncertainty in Artificial Intelligence, 819-828, 2023 | 1 | 2023 |
| Advances in Sampling and Counting Bipartite Matchings and Directed Acyclic Graphs J Harviainen Helsingin yliopisto, 2024 | | 2024 |
| Faster Perfect Sampling of Bayesian Network Structures J Harviainen, M Koivisto The 40th Conference on Uncertainty in Artificial Intelligence, 2024 | | 2024 |
| Estimating the Permanent by Nesting Importance Sampling J Harviainen, M Koivisto Forty-first International Conference on Machine Learning, 2024 | | 2024 |
| A Faster Practical Approximation Scheme for the Permanent J Harviainen, M Koivisto Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 12216 …, 2023 | | 2023 |
| Quantum Speedups for Bayesian Network Structure Learning J Harviainen, K Rychkova, M Koivisto arXiv preprint arXiv:2305.19673, 2023 | | 2023 |
| Trustworthy Monte Carlo J Harviainen, M Koivisto, P Kaski Advances in Neural Information Processing Systems, 2022 | | 2022 |
| Approximating the Permanent of a Matrix with Deep Rejection Sampling J Harviainen Helsingin yliopisto, 2021 | | 2021 |
