Artem Babenko

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy.

[BibT_eX]

[DOI]

Oleg Platonov

Denis Kuznedelev

CoRR, 2022

Revisiting Pretraining Objectives for Tabular Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2022

On Embeddings for Numerical Features in Tabular Deep Learning.

[BibT_eX]

[DOI]

Yury Gorishniy

Ivan Rubachev

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When, Why, and Which Pretrained GANs Are Useful?

[BibT_eX]

[DOI]

Timofey Grigoryev

Proceedings of the Tenth International Conference on Learning Representations, 2022

Label-Efficient Semantic Segmentation with Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Distilling the Knowledge from Normalizing Flows.

[BibT_eX]

[DOI]

Dmitry Baranchuk

Vladimir Aliev

CoRR, 2021

Disentangled Representations from Non-Disentangled Models.

[BibT_eX]

[DOI]

CoRR, 2021

Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search.

[BibT_eX]

[DOI]

Harsha Vardhan Simhadri

Ravishankar Krishnaswamy

Gopal Srinivasa

Suhas Jayaram Subramanya

Jingdong Wang

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Revisiting Deep Learning Models for Tabular Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Object Segmentation Without Labels with Large-Scale Generative Models.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Functional Space Analysis of Local GAN Convergence.

[BibT_eX]

[DOI]

Valentin Khrulkov

Ivan V. Oseledets

Proceedings of the 38th International Conference on Machine Learning, 2021

On Self-Supervised Image Representations for GAN Evaluation.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Latent Transformations via NeuralODEs for GAN-based Image Editing.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Valentin Khrulkov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Navigating the GAN Parameter Space for Semantic Image Editing.

[BibT_eX]

[DOI]

Anton Cherepkov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models.

[BibT_eX]

[DOI]

CoRR, 2020

Unsupervised Discovery of Interpretable Directions in the GAN Latent Space.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Editable Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data.

[BibT_eX]

[DOI]

Sergei Popov

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

RPGAN: GANs Interpretability via Random Routing.

[BibT_eX]

[DOI]

CoRR, 2019

Towards Similarity Graphs Constructed by Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Dmitry Baranchuk

CoRR, 2019

Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs.

[BibT_eX]

[DOI]

CoRR, 2019

Relevance Proximity Graphs for Fast Relevance Retrieval.

[BibT_eX]

[DOI]

CoRR, 2019

Beyond Vector Spaces: Compact Data Representation as Differentiable Weighted Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning to Route in Similarity Graphs.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Unsupervised Neural Quantization for Compressed-Domain Similarity Search.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Impostor Networks for Fast Fine-Grained Recognition.

[BibT_eX]

[DOI]

Vadim Lebedev

CoRR, 2018

Non-metric Similarity Graphs for Maximum Inner Product Search.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors.

[BibT_eX]

[DOI]

Dmitry Baranchuk

Yury Malkov

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

AnnArbor: Approximate Nearest Neighbors Using Arborescence Coding.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2017

Product Split Trees.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Pairwise Quantization.

[BibT_eX]

[DOI]

Relja Arandjelovic

CoRR, 2016

Efficient Indexing of Billion-Scale Datasets of Deep Descriptors.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

The Inverted Multi-Index.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Aggregating Deep Convolutional Features for Image Retrieval.

[BibT_eX]

[DOI]

CoRR, 2015

Aggregating Local Deep Features for Image Retrieval.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Tree quantization for large-scale similarity search and classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Improving Bilayer Product Quantization for Billion-Scale Approximate Nearest Neighbors in High Dimensions.

[BibT_eX]

[DOI]

CoRR, 2014

Neural Codes for Image Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2014, 2014

Additive Quantization for Extreme Vector Compression.

[BibT_eX]

[DOI]