 Binary Losses for Density Ratio EstimationInternational Conference on Learning Representations (ICLR), 2024 |
 NRGBoost: Energy-Based Generative Boosted TreesInternational Conference on Learning Representations (ICLR), 2024 João Bravo |
 Image Inpainting via Tractable Steering of Diffusion ModelsInternational Conference on Learning Representations (ICLR), 2023 |
 Compositional Sculpting of Iterative Generative ProcessesNeural Information Processing Systems (NeurIPS), 2023 |
 Precision-Recall Divergence Optimization for Generative Modeling with
GANs and Normalizing FlowsNeural Information Processing Systems (NeurIPS), 2023 |
 Synthetic data, real errors: how (not) to publish and use synthetic dataInternational Conference on Machine Learning (ICML), 2023 |
 Tractable Control for Autoregressive Language GenerationInternational Conference on Machine Learning (ICML), 2023 |
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 DCTRGAN: Improving the Precision of Generative Models with ReweightingJournal of Instrumentation (JINST), 2020 |
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 Fair Generative Modeling via Weak SupervisionInternational Conference on Machine Learning (ICML), 2019 |
 Bridging the Gap Between -GANs and Wasserstein GANsInternational Conference on Machine Learning (ICML), 2019 |
 Understanding the Limitations of Variational Mutual Information
EstimatorsInternational Conference on Learning Representations (ICLR), 2019 |
 Greedy Convex EnsembleInternational Joint Conference on Artificial Intelligence (IJCAI), 2019 |
 Neural Network based Explicit Mixture Models and
Expectation-maximization based LearningIEEE International Joint Conference on Neural Network (IJCNN), 2019 |
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 Rethinking Generative Mode Coverage: A Pointwise Guaranteed ApproachNeural Information Processing Systems (NeurIPS), 2019 |
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 AdaGAN: Boosting Generative ModelsNeural Information Processing Systems (NeurIPS), 2017 |
