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Journal Articles
- 2017
[j1]Natasa Tagasovska, Periklis Andritsos:
Distributed clustering of categorical data using the information bottleneck framework. Inf. Syst. 72: 161-178 (2017)
Conference and Workshop Papers
- 2024
- [c8]Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho:
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. ICML 2024 - 2023
- [c7]Natasa Tagasovska, Firat Ozdemir, Axel Brando:
Retrospective Uncertainties for Deep Models using Vine Copulas. AISTATS 2023: 7528-7539 - [c6]Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev:
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling. CLeaR 2023: 662-691 - 2022
- [c5]Yanan Xin
, Natasa Tagasovska, Fernando Pérez-Cruz, Martin Raubal:
Vision paper: causal inference for interpretable and robust machine learning in mobility analysis. SIGSPATIAL/GIS 2022: 66:1-66:4 - 2020
- [c4]Natasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter:
Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery. ICML 2020: 9311-9323 - [c3]Damien Ackerer, Natasa Tagasovska, Thibault Vatter:
Deep Smoothing of the Implied Volatility Surface. NeurIPS 2020 - 2019
- [c2]Natasa Tagasovska, David Lopez-Paz:
Single-Model Uncertainties for Deep Learning. NeurIPS 2019: 6414-6425 - [c1]Natasa Tagasovska, Damien Ackerer, Thibault Vatter:
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders. NeurIPS 2019: 6525-6537
Informal and Other Publications
- 2024
- [i14]Natasa Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas:
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient. CoRR abs/2405.18075 (2024) - [i13]Anna Susmelj, Mael Macuglia, Natasa Tagasovska, Reto Sutter, Sebastiano Caprara, Jean-Philippe Thiran, Ender Konukoglu:
Uncertainty modeling for fine-tuned implicit functions. CoRR abs/2406.12082 (2024) - [i12]Natasa Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian Rokkum Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho:
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design. CoRR abs/2407.21028 (2024) - 2023
- [i11]Natasa Tagasovska, Firat Ozdemir, Axel Brando:
Retrospective Uncertainties for Deep Models using Vine Copulas. CoRR abs/2302.12606 (2023) - [i10]Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho:
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. CoRR abs/2306.00344 (2023) - [i9]Michael Maser, Natasa Tagasovska, Jae Hyeon Lee, Andrew M. Watkins:
MoleCLUEs: Optimizing Molecular Conformers by Minimization of Differentiable Uncertainty. CoRR abs/2306.11681 (2023) - 2022
- [i8]Yanan Xin, Natasa Tagasovska, Fernando Pérez-Cruz, Martin Raubal:
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis. CoRR abs/2210.10010 (2022) - [i7]Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hötzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic:
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences. CoRR abs/2210.10838 (2022) - [i6]Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev:
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling. CoRR abs/2211.03553 (2022) - 2021
- [i5]Radhakrishna Achanta, Natasa Tagasovska:
Uncertainty Surrogates for Deep Learning. CoRR abs/2104.08147 (2021) - 2019
- [i4]Damien Ackerer, Natasa Tagasovska, Thibault Vatter:
Deep Smoothing of the Implied Volatility Surface. CoRR abs/1906.05065 (2019) - [i3]Natasa Tagasovska, Damien Ackerer, Thibault Vatter:
Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders. CoRR abs/1906.05423 (2019) - 2018
- [i2]Natasa Tagasovska, David Lopez-Paz:
Frequentist uncertainty estimates for deep learning. CoRR abs/1811.00908 (2018) - [i1]Vaibhav Kulkarni, Natasa Tagasovska, Thibault Vatter, Benoît Garbinato:
Generative Models for Simulating Mobility Trajectories. CoRR abs/1811.12801 (2018)
Coauthor Index
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