Tagasovska, Natasa

14 publications

NeurIPS 2025 Generative Property Enhancer: Implicit Guided Generation Through Conditional Density Estimation Pedro O. Pinheiro, Pan Kessel, Aya Abdelsalam Ismail, Sai Pooja Mahajan, Kyunghyun Cho, Saeed Saremi, Natasa Tagasovska

ICLRW 2025 Supervised Contrastive Block Disentanglement Taro Makino, Ji Won Park, Natasa Tagasovska, Takamasa Kudo, Paula Coelho, Heming Yao, Jan-Christian Huetter, Ana Carolina Leote, Burkhard Hoeckendorf, Stephen Ra, David Richmond, Kyunghyun Cho, Aviv Regev, Romain Lopez

ICLR 2025 Uncertainty Modeling for Fine-Tuned Implicit Functions Anna Susmelj, Mael Macuglia, Natasa Tagasovska, Reto Sutter, Sebastiano Caprara, Jean-Philippe Thiran, Ender Konukoglu

ICML 2024 BOtied: Multi-Objective Bayesian Optimization with Tied Multivariate Ranks Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho

NeurIPS 2024 Implicitly Guided Design with PropEn: Match Your Data to Follow the Gradient Nataša Tagasovska, Vladimir Gligorijević, Kyunghyun Cho, Andreas Loukas

CLeaR 2023 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

NeurIPSW 2023 MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Models Michael Maser, Natasa Tagasovska, Jae Hyeon Lee, Andrew Martin Watkins

AISTATS 2023 Retrospective Uncertainties for Deep Models Using Vine Copulas Natasa Tagasovska, Firat Ozdemir, Axel Brando

NeurIPSW 2022 A Pareto-Optimal Compositional Energy-Based Model for Sampling and Optimization of Protein Sequences Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hotzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic

NeurIPSW 2022 Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan Pritchard, Aviv Regev

NeurIPS 2020 Deep Smoothing of the Implied Volatility Surface Damien Ackerer, Natasa Tagasovska, Thibault Vatter

ICML 2020 Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery Natasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter

NeurIPS 2019 Copulas as High-Dimensional Generative Models: Vine Copula Autoencoders Natasa Tagasovska, Damien Ackerer, Thibault Vatter

NeurIPS 2019 Single-Model Uncertainties for Deep Learning Natasa Tagasovska, David Lopez-Paz