Dmitry Baranchuk

According to our database1, Dmitry Baranchuk authored at least 19 papers between 2018 and 2024.

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Bibliography

2024
Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization.
CoRR, 2024

Results of the Big ANN: NeurIPS'23 competition.
CoRR, 2024

Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization.
CoRR, 2024

Invertible Consistency Distillation for Text-Guided Image Editing in Around 7 Steps.
CoRR, 2024

Your Student is Better than Expected: Adaptive Teacher-Student Collaboration for Text-Conditional Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

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

Distributed Inference and Fine-tuning of Large Language Models Over The Internet.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

TabDDPM: Modelling Tabular Data with Diffusion Models.
Proceedings of the International Conference on Machine Learning, 2023

DeDrift: Robust Similarity Search under Content Drift.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Petals: Collaborative Inference and Fine-tuning of Large Models.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023

2022
Petals: Collaborative Inference and Fine-tuning of Large Models.
CoRR, 2022

Graph-based Nearest Neighbor Search in Hyperbolic Spaces.
Proceedings of the Tenth International Conference on Learning Representations, 2022

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

2021
Distilling the Knowledge from Normalizing Flows.
CoRR, 2021

Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

2020
GP-VAE: Deep Probabilistic Time Series Imputation.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Towards Similarity Graphs Constructed by Deep Reinforcement Learning.
CoRR, 2019

Learning to Route in Similarity Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors.
Proceedings of the Computer Vision - ECCV 2018, 2018


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