Valentin Khrulkov

According to our database1, Valentin Khrulkov authored at least 23 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2023
Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models.
CoRR, 2023

Understanding DDPM Latent Codes Through Optimal Transport.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Understanding DDPM Latent Codes Through Optimal Transport.
CoRR, 2022

Label-Efficient Semantic Segmentation with Diffusion Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Hyperbolic Vision Transformers: Combining Improvements in Metric Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Disentangled Representations from Non-Disentangled Models.
CoRR, 2021

Revisiting Deep Learning Models for Tabular Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Functional Space Analysis of Local GAN Convergence.
Proceedings of the 38th International Conference on Machine Learning, 2021

Latent Transformations via NeuralODEs for GAN-based Image Editing.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Neural Side-by-Side: Predicting Human Preferences for No-Reference Super-Resolution Evaluation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Tensor Train Decomposition on TensorFlow (T3F).
J. Mach. Learn. Res., 2020

Sample Efficient Ensemble Learning with Catalyst.RL.
CoRR, 2020

Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks.
Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Tensorized Embedding Layers.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Hyperbolic Image Embeddings.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Universality Theorems for Generative Models.
CoRR, 2019

Tensorized Embedding Layers for Efficient Model Compression.
CoRR, 2019

Generalized Tensor Models for Recurrent Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Desingularization of Bounded-Rank Matrix Sets.
SIAM J. Matrix Anal. Appl., 2018

Geometry Score: A Method For Comparing Generative Adversarial Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Expressive power of recurrent neural networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Art of Singular Vectors and Universal Adversarial Perturbations.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Vico-Greengard-Ferrando quadratures in the tensor solver for integral equations.
CoRR, 2017


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