3 citations · 6 across the 6 of their papers we have counts for
7 papers
Prompt-Consistency Inference for Zero-Shot Flow-Matching Text-to-Speech Models
Vasily Zadorozhnyy, Can Goksen, Kazuhito Koishida +1
In recent years, flow-matching models have produced significant improvements in zero-shot text-to-speech synthesis. Conditioned on an audio prompt and text, these models learn a ve…
GFM4MPM: Towards Geospatial Foundation Models for Mineral Prospectivity Mapping
Angel Daruna, Vasily Zadorozhnyy, Georgina Lukoczki +1
Machine Learning (ML) for Mineral Prospectivity Mapping (MPM) remains a challenging problem as it requires the analysis of associations between large-scale multi-modal geospatial d…
SCP-GAN: Self-Correcting Discriminator Optimization for Training Consistency Preserving Metric GAN on Speech Enhancement Tasks
Vasily Zadorozhnyy, Qiang Ye, Kazuhito Koishida
In recent years, Generative Adversarial Networks (GANs) have produced significantly improved results in speech enhancement (SE) tasks. They are difficult to train, however. In this…
Breaking Time Invariance: Assorted-Time Normalization for RNNs
Cole Pospisil, Vasily Zadorozhnyy, Qiang Ye
Methods such as Layer Normalization (LN) and Batch Normalization (BN) have proven to be effective in improving the training of Recurrent Neural Networks (RNNs). However, existing m…
Orthogonal Gated Recurrent Unit with Neumann-Cayley Transformation
Edison Mucllari, Vasily Zadorozhnyy, Cole Pospisil +2
In recent years, using orthogonal matrices has been shown to be a promising approach in improving Recurrent Neural Networks (RNNs) with training, stability, and convergence, partic…
Symmetry Structured Convolutional Neural Networks
Kehelwala Dewage Gayan Maduranga, Vasily Zadorozhnyy, Qiang Ye
We consider Convolutional Neural Networks (CNNs) with 2D structured features that are symmetric in the spatial dimensions. Such networks arise in modeling pairwise relationships fo…
Adaptive Weighted Discriminator for Training Generative Adversarial Networks
Vasily Zadorozhnyy, Qiang Cheng, Qiang Ye
Generative adversarial network (GAN) has become one of the most important neural network models for classical unsupervised machine learning. A variety of discriminator loss functio…