Teodora Pandeva

According to our database, Teodora Pandeva authored at least 10 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster.

Grigory Bartosh, Teodora Pandeva, Sushrut Karmalkar, Javier Zazo

CoRR, May, 2026

2025

E-Scores for (In)Correctness Assessment of Generative Model Outputs.

Guneet S. Dhillon, Javier González, Teodora Pandeva, Alicia Curth

CoRR, October, 2025

Parallel Sampling from Masked Diffusion Models via Conditional Independence Testing.

Iskander Azangulov, Teodora Pandeva, Niranjani Prasad, Javier Zazo, Sushrut Karmalkar

CoRR, October, 2025

A Fourier Space Perspective on Diffusion Models.

Fabian Falck, Teodora Pandeva, Kiarash Zahirnia, Rachel Lawrence, Richard E. Turner, Edward Meeds, Javier Zazo, Sushrut Karmalkar

CoRR, May, 2025

Robust Multi-view Co-expression Network Inference.

Teodora Pandeva, Martijs Jonker, Leendert Hamoen, Joris M. Mooij, Patrick Forré

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

2024

E-Valuating Classifier Two-Sample Tests.

Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré

Trans. Mach. Learn. Res., 2024

longmixr: a tool for robust clustering of high-dimensional cross-sectional and longitudinal variables of mixed data types.

Jonas Hagenberg, Monika Budde, Teodora Pandeva, Ivan Kondofersky, Sabrina K. Schaupp, Fabian J. Theis, Thomas G. Schulze, Nikola S. Müller, Urs Heilbronner, Richa Batra, Janine Knauer-Arloth

Bioinform., 2024

Deep anytime-valid hypothesis testing.

Teodora Pandeva, Patrick Forré, Aaditya Ramdas, Shubhanshu Shekhar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Multi-View Independent Component Analysis with Shared and Individual Sources.

Teodora Pandeva, Patrick Forré

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2019

MMGAN: Generative Adversarial Networks for Multi-Modal Distributions.

Teodora Pandeva, Matthias Schubert

CoRR, 2019