Multilingual Factor Analysis. - Francisco Vargas 001; Kamen Brestnichki; Alex Papadopoulos-Korfiatis; Nils Hammerla (ACL (1), 2019)

Model Comparison for Semantic Grouping. - Francisco Vargas 001; Kamen Brestnichki; Nils Hammerla (ICML, 2019)

Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation. - Francisco Vargas 001; Ryan Cotterell (EMNLP (1), 2020)

Efficient Representations for Privacy-Preserving Inference. - Han Xuanyuan; Francisco Vargas 001; Stephen Cummins (CoRR, 2021)

Solving Schrödinger Bridges via Maximum Likelihood. - Francisco Vargas 001; Pierre Thodoroff; Austen Lamacraft; Neil D. Lawrence (Entropy, 2021)

Adversarial Concept Erasure in Kernel Space. - Shauli Ravfogel; Francisco Vargas 001; Yoav Goldberg; Ryan Cotterell (EMNLP, 2022)

Denoising Diffusion Samplers. - Francisco Vargas 001; Will Sussman Grathwohl; Arnaud Doucet (ICLR, 2023)

Dimensionality Reduction as Probabilistic Inference. - Aditya Ravuri; Francisco Vargas 001; Vidhi Lalchand; Neil D. Lawrence (CoRR, 2023)

Expressiveness Remarks for Denoising Diffusion Models and Samplers. - Francisco Vargas 001; Teodora Reu; Anna Kerekes (CoRR, 2023)

Transport, Variational Inference and Diffusions: with Applications to Annealed Flows and Schrödinger Bridges. - Francisco Vargas 001; Nikolas Nüsken (CoRR, 2023)

A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. - Kieran Didi; Francisco Vargas 001; Simon V. Mathis; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2023)

Bayesian learning via neural Schrödinger-Föllmer flows. - Francisco Vargas 001; Andrius Ovsianas; David Fernandes; Mark Girolami; Neil D. Lawrence; Nikolas Nüsken (Stat. Comput., 2023)

Correction: Vargas et al. Solving Schrödinger Bridges via Maximum Likelihood. Entropy 2021, 23, 1134. - Francisco Vargas 001; Pierre Thodoroff; Austen Lamacraft; Neil D. Lawrence (Entropy, 2023)

Transport meets Variational Inference: Controlled Monte Carlo Diffusions. - Francisco Vargas 001; Shreyas Padhy; Denis Blessing; Nikolas Nüsken (ICLR, 2024)

Dynamics-Informed Protein Design with Structure Conditioning. - Urszula Julia Komorowska; Simon V. Mathis; Kieran Didi; Francisco Vargas 001; Pietro Lio; Mateja Jamnik (ICLR, 2024)

Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling. - Denis Blessing; Xiaogang Jia; Johannes Esslinger; Francisco Vargas 001; Gerhard Neumann (ICML, 2024)

DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Riccardo Barbano; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lió (NeurIPS, 2024)

To smooth a cloud or to pin it down: Expressiveness guarantees and insights on score matching in denoising diffusion models. - Teodora Reu; Francisco Vargas 001; Anna Kerekes; Michael M. Bronstein (UAI, 2024)

DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Vincent Dutordoir; Riccardo Barbano; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2024)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models. - Paulina Kulyte; Francisco Vargas 001; Simon Valentin Mathis; Yu Guang Wang 001; José Miguel Hernández-Lobato; Pietro Liò (CoRR, 2024)

Iterative Importance Fine-tuning of Diffusion Models. - Alexander Denker; Shreyas Padhy; Francisco Vargas 001; Johannes Hertrich (CoRR, 2025)

Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo. - Cheuk Kit Lee; Paul Jeha; Jes Frellsen; Pietro Lio; Michael Samuel Albergo; Francisco Vargas 001 (CoRR, 2025)

No Trick, No Treat: Pursuits and Challenges Towards Simulation-free Training of Neural Samplers. - Jiajun He 003; Yuanqi Du; Francisco Vargas 001; Dinghuai Zhang; Shreyas Padhy; Ruikang Ouyang; Carla P. Gomes; José Miguel Hernández-Lobato (CoRR, 2025)

FEAT: Free energy Estimators with Adaptive Transport. - Jiajun He 003; Yuanqi Du; Francisco Vargas 001; Yuanqing Wang; Carla P. Gomes; José Miguel Hernández-Lobato; Eric Vanden-Eijnden (CoRR, 2025)

RNE: a plug-and-play framework for diffusion density estimation and inference-time control. - Jiajun He 003; José Miguel Hernández-Lobato; Yuanqi Du; Francisco Vargas 001 (CoRR, 2025)

Path Integral Optimiser: Global Optimisation via Neural Schrödinger-Föllmer Diffusion. - Max McGuinness; Eirik Fladmark; Francisco Vargas 001 (CoRR, 2025)