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2020 – today
- 2024
[c4]Alexandra Maria Hotti, Lennart Alexander Van der Goten, Jens Lagergren:
Benefits of Non-Linear Scale Parameterizations in Black Box Variational Inference through Smoothness Results and Gradient Variance Bounds. AISTATS 2024: 3538-3546- [c3]Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, Jens Lagergren:
Efficient Mixture Learning in Black-Box Variational Inference. ICML 2024 - [c2]Alfred Nilsson, Klas Wijk, Sai Bharath Chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, Hossein Azizpour:
Indirectly Parameterized Concrete Autoencoders. ICML 2024 - [i4]Alfred Nilsson, Klas Wijk, Sai Bharath Chandra Gutha, Erik Englesson, Alexandra Hotti, Carlo Saccardi, Oskar Kviman, Jens Lagergren, Ricardo Vinuesa, Hossein Azizpour:
Indirectly Parameterized Concrete Autoencoders. CoRR abs/2403.00563 (2024) - [i3]Alexandra Hotti, Oskar Kviman, Ricky Molén, Víctor Elvira, Jens Lagergren:
Efficient Mixture Learning in Black-Box Variational Inference. CoRR abs/2406.07083 (2024) - 2023
- [c1]Oskar Kviman, Ricky Molén
, Alexandra Hotti, Semih Kurt, Víctor Elvira, Jens Lagergren:
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders. ICML 2023: 18008-18022 - 2022
- [i2]Oskar Kviman, Ricky Molén, Alexandra Hotti, Semih Kurt, Víctor Elvira, Jens Lagergren:
Learning with MISELBO: The Mixture Cookbook. CoRR abs/2209.15514 (2022) - 2021
- [i1]Alexandra Hotti, Riccardo Sven Risuleo, Stefan Magureanu, Aref Moradi, Jens Lagergren:
The Klarna Product Page Dataset: A Realistic Benchmark for Web Representation Learning. CoRR abs/2111.02168 (2021)
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