Tomas Geffner
16 papers · 2018–2025 · 4 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (23) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🧬
Topic Evolution
🏆
Keyword Champion
(4)
🧭
Keyword Pioneer
🗃️
Keyword Collector
(79)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
⚡
Prolific Year · Productive
Venues
Top co-authors
Research topics
Deep Learning
(15)
Models
(15)
Machine Learning
(12)
Optimization & Theory
(11)
Artificial Intelligence
(4)
Bayesian & Probabilistic · Machine Learning
(4)
Bayesian & Probabilistic · Artificial Intelligence
(3)
Architectures
(2)
Learning Types · Deep Learning
(2)
Computer Vision
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Core AI
(1)
Learning Types · Machine Learning
(1)
Keywords
variational inference
(10)
control variate
(4)
diffusion model
(3)
flow matching
(2)
variance reduction
(2)
reparameterization gradient
(2)
gradient estimator
(2)
gradient variance
(2)
markov chain monte carlo
(2)
bayesian inference
(1)
langevin dynamics
(1)
high-dimensional inference
(1)
posterior distribution
(1)
hierarchical model
(1)
preference optimization
(1)
approximate inference
(1)
monte carlo sampling
(1)
posterior estimation
(1)
importance weighting
(1)
language modeling
(1)
Papers
Adaptive Flow Matching for Resolving Small-Scale Physics
ICML 2025
Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
ICML 2025
Energy-Based Diffusion Language Models for Text Generation
ICLR 2025
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
ICLR 2025
Proteina: Scaling Flow-based Protein Structure Generative Models
ICLR 2025
Truncated Consistency Models
ICLR 2025
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
NeurIPS 2024
Joint control variate for faster black-box variational inference
AISTATS 2024
Compositional Score Modeling for Simulation-Based Inference
ICML 2023
Langevin Diffusion Variational Inference
AISTATS 2023
Variational Inference with Locally Enhanced Bounds for Hierarchical Models
ICML 2022
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
NeurIPS 2021
On the difficulty of unbiased alpha divergence minimization
ICML 2021
Approximation Based Variance Reduction for Reparameterization Gradients
NeurIPS 2020
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
AISTATS 2020
Using Large Ensembles of Control Variates for Variational Inference
NeurIPS 2018