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04/10/2023
Towards Real-time Text-driven Image Manipulation with Unconditional Diffusion Models
Recent advances in diffusion models enable many powerful instruments for...
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03/21/2022
Hyperbolic Vision Transformers: Combining Improvements in Metric Learning
Metric learning aims to learn a highly discriminative model encouraging ...
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02/14/2022
Understanding DDPM Latent Codes Through Optimal Transport
Diffusion models have recently outperformed alternative approaches to mo...
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12/06/2021
Label-Efficient Semantic Segmentation with Diffusion Models
Denoising diffusion probabilistic models have recently received much res...
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11/29/2021
Latent Transformations via NeuralODEs for GAN-based Image Editing
Recent advances in high-fidelity semantic image editing heavily rely on ...
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06/22/2021
Revisiting Deep Learning Models for Tabular Data
The necessity of deep learning for tabular data is still an unanswered q...
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02/11/2021
Disentangled Representations from Non-Disentangled Models
Constructing disentangled representations is known to be a difficult tas...
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02/08/2021
Functional Space Analysis of Local GAN Convergence
Recent work demonstrated the benefits of studying continuous-time dynami...
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08/15/2020
Performance of Hyperbolic Geometry Models on Top-N Recommendation Tasks
We introduce a simple autoencoder based on hyperbolic geometry for solvi...
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03/29/2020
Sample Efficient Ensemble Learning with Catalyst.RL
We present Catalyst.RL, an open-source PyTorch framework for reproducibl...
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05/27/2019
Universality Theorems for Generative Models
Despite the fact that generative models are extremely successful in prac...
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04/03/2019
Hyperbolic Image Embeddings
Computer vision tasks such as image classification, image retrieval and ...
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01/30/2019
Generalized Tensor Models for Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are very successful at solving challeng...
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01/30/2019
Tensorized Embedding Layers for Efficient Model Compression
The embedding layers transforming input words into real vectors are the ...
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02/07/2018
Geometry Score: A Method For Comparing Generative Adversarial Networks
One of the biggest challenges in the research of generative adversarial ...
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01/05/2018
Tensor Train decomposition on TensorFlow (T3F)
Tensor Train decomposition is used across many branches of machine learn...
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09/11/2017
Art of singular vectors and universal adversarial perturbations
Vulnerability of Deep Neural Networks (DNNs) to adversarial attacks has ...
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04/05/2017