Research output per year
Research output per year
- 14 results
Search results
-
2025
Improving 3D Reconstruction Through RGB-D Sensor Noise Modeling
Afzal Maken, F., Muthu, S., Nguyen, C., Sun, C., Tong, J., Wang, S., Tsuchida, R., Howard, D., Dunstall, S. & Petersson, L., 5 Feb 2025, In: Sensors. 25, 3, 17 p., 950.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile1 Citation (Scopus) -
2024
Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families
Tsuchida, R., Ong, C. S. & Sejdinovic, D., 2024, Thirty-Eighth AAAI Conference on Artificial Intelligence. Washington DC USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 20559-20566 8 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 18).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access2 Citations (Scopus) -
Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach
Ye, C., Tsuchida, R., Petersson, L. & Barnes, N., 2024, Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024. Mortensen, E. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 1062-1071 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
1 Citation (Scopus) -
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
Khamis, A., Tsuchida, R., Tarek, M., Rolland, V. & Petersson, L., 20 Mar 2024, (Accepted/In press) In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 20 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access11 Citations (Scopus) -
2023
Deep Equilibrium Models as Estimators for Continuous Latent Variables
Tsuchida, R. & Ong, C. S., 2023, Proceedings of The 26th International Conference on Artificial Intelligence and Statistics. Ruiz, F., Dy, J. & van de Meent, J.-W. (eds.). London UK: Proceedings of Machine Learning Research (PMLR), Vol. 206. p. 1646-1671 26 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access5 Citations (Scopus) -
Squared Neural Families: A New Class of Tractable Density Models
Tsuchida, R., Ong, C. S. & Sejdinovic, D., 2023, Advances in Neural Information Processing Systems 36 pre-proceedings (NeurIPS 2023). Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). San Diego CA USA: Neural Information Processing Systems (NIPS), 26 p. (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access6 Citations (Scopus) -
Stochastic gradient updates yield deep equilibrium kernels
Tsuchida, R. & Ong, C. S., 2023, In: Transactions on Machine Learning Research. 2023, 21 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access -
2022
DECLARATIVE NETS THAT ARE EQUILIBRIUM MODELS
Tsuchida, R., Yong, S. Y., Armin, M. A., Petersson, L. & Ong, C. S., 2022, The Tenth International Conference on Learning Representations. LeCun, Y. (ed.). USA: International Conference on Learning Representations (ICLR)Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access4 Citations (Scopus) -
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning
Ye, C., Barnes, N., Petersson, L. & Tsuchida, R., 2022, 2022 26th International Conference on Pattern Recognition, ICPR 2022. Jenkin, M., I. Christensen, H. & Liu, C.-L. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 2078-2085 8 p. (Proceedings - International Conference on Pattern Recognition; vol. 2022-August).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
3 Citations (Scopus) -
Gaussian Process Bandits with Aggregated Feedback
Zhang, M., Tsuchida, R. & Ong, C. S., 2022, Thirty-Sixth AAAI Conference on Artificial Intelligence. Honavar, V. & Spaan, M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 9074-9081 8 p. (Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access3 Citations (Scopus) -
2021
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks
Tsuchida, R., Pearce, T., van der Heide, C., Roosta, F. & Gallagher, M., 2021, The Thirty-Fifth AAAI Conference on Artificial Intelligence. Leyton-Brown, K. & M. (eds.). Palo Alto CA USA: Association for the Advancement of Artificial Intelligence (AAAI), p. 9967-9977 11 p. (35th AAAI Conference on Artificial Intelligence, AAAI 2021; vol. 35, no. 11).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access5 Citations (Scopus) -
2019
Exchangeability and kernel invariance in trained MLPs
Tsuchida, R., Roosta, F. & Gallagher, M., 2019, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. Kraus, S. (ed.). Marina del Rey CA USA: International Joint Conferences on Artificial Intelligence, p. 3592-3598 7 p. (IJCAI International Joint Conference on Artificial Intelligence; vol. 2019-August).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access2 Citations (Scopus) -
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions
Pearce, T., Tsuchida, R., Zaki, M., Brintrup, A. & Neely, A., 2019, The 35th Uncertainty in Artificial Intelligence Conference. Rahman, T. (ed.). Dallas Texas USA: AUAI Press, Vol. 115. p. 134-144 11 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access9 Citations (Scopus) -
2018
Invariance of weight distributions in rectified MLPs
Tsuchida, R., Roosta-Khorasani, F. & Gallagher, M., 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), p. 7962-7974 13 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
10 Citations (Scopus)