Search Results for author: Yaroslav Ganin

Found 14 papers, 8 papers with code

Continuous diffusion for categorical data

no code implementations28 Nov 2022 Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler

Diffusion models have quickly become the go-to paradigm for generative modelling of perceptual signals (such as images and sound) through iterative refinement.

Language Modelling

Computer-Aided Design as Language

no code implementations NeurIPS 2021 Yaroslav Ganin, Sergey Bartunov, Yujia Li, Ethan Keller, Stefano Saliceti

Computer-Aided Design (CAD) applications are used in manufacturing to model everything from coffee mugs to sports cars.

Language Modelling Translation

PolyGen: An Autoregressive Generative Model of 3D Meshes

1 code implementation ICML 2020 Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia

Polygon meshes are an efficient representation of 3D geometry, and are of central importance in computer graphics, robotics and games development.

3D Shape Generation Surface Reconstruction

GibbsNet: Iterative Adversarial Inference for Deep Graphical Models

no code implementations NeurIPS 2017 Alex Lamb, Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron Courville, Yoshua Bengio

Directed latent variable models that formulate the joint distribution as $p(x, z) = p(z) p(x \mid z)$ have the advantage of fast and exact sampling.


Domain-Adversarial Training of Neural Networks

35 code implementations28 May 2015 Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, Victor Lempitsky

Our approach is directly inspired by the theory on domain adaptation suggesting that, for effective domain transfer to be achieved, predictions must be made based on features that cannot discriminate between the training (source) and test (target) domains.

Domain Generalization General Classification +5

Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition

10 code implementations19 Dec 2014 Vadim Lebedev, Yaroslav Ganin, Maksim Rakhuba, Ivan Oseledets, Victor Lempitsky

We propose a simple two-step approach for speeding up convolution layers within large convolutional neural networks based on tensor decomposition and discriminative fine-tuning.

General Classification Tensor Decomposition

Unsupervised Domain Adaptation by Backpropagation

21 code implementations26 Sep 2014 Yaroslav Ganin, Victor Lempitsky

Here, we propose a new approach to domain adaptation in deep architectures that can be trained on large amount of labeled data from the source domain and large amount of unlabeled data from the target domain (no labeled target-domain data is necessary).

Image Classification Multi-target Domain Adaptation +3

$ N^4 $-Fields: Neural Network Nearest Neighbor Fields for Image Transforms

no code implementations25 Jun 2014 Yaroslav Ganin, Victor Lempitsky

We propose a new architecture for difficult image processing operations, such as natural edge detection or thin object segmentation.

Edge Detection Semantic Segmentation

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