Evgenii Zheltonozhskii | DeepAI

DeepAI AI Chat

Featured Co-authors

Jia Li
149 publications
Raja Giryes
106 publications
Wenhao Yu
66 publications
Or Litany
50 publications
Siva Reddy
45 publications
Alex M. Bronstein
43 publications
Qian Liu
38 publications
Dzmitry Bahdanau
35 publications
Yacine Jernite
32 publications
Chaim Baskin
29 publications
Daniel Fried
29 publications

∙ 08/26/2023

Semi-Supervised Semantic Segmentation via Marginal Contextual Information

We present a novel confidence refinement scheme that enhances pseudo-lab...

0 Moshe Kimhi, et al. ∙

∙ 05/09/2023

StarCoder: may the source be with you!

The BigCode community, an open-scientific collaboration working on the r...

12 Raymond Li, et al. ∙

∙ 06/13/2022

GoToNet: Fast Monocular Scene Exposure and Exploration

Autonomous scene exposure and exploration, especially in localization or...

4 Tom Avrech, et al. ∙

∙ 01/30/2022

On Recoverability of Graph Neural Network Representations

Despite their growing popularity, graph neural networks (GNNs) still hav...

2 Maxim Fishman, et al. ∙

∙ 11/29/2021

End-to-End Referring Video Object Segmentation with Multimodal Transformers

The referring video object segmentation task (RVOS) involves segmentatio...

10 Adam Botach, et al. ∙

∙ 03/25/2021

Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels

The success of learning with noisy labels (LNL) methods relies heavily o...

4 Evgenii Zheltonozhskii, et al. ∙

∙ 11/06/2020

Single-Node Attack for Fooling Graph Neural Networks

Graph neural networks (GNNs) have shown broad applicability in a variety...

7 Ben Finkelshtein, et al. ∙

∙ 08/24/2020

Self-Supervised Learning for Large-Scale Unsupervised Image Clustering

Unsupervised learning has always been appealing to machine learning rese...

8 Evgenii Zheltonozhskii, et al. ∙

∙ 04/19/2020

HCM: Hardware-Aware Complexity Metric for Neural Network Architectures

Convolutional Neural Networks (CNNs) have become common in many fields i...

0 Alex Karbachevsky, et al. ∙

∙ 03/04/2020

Colored Noise Injection for Training Adversarially Robust Neural Networks

Even though deep learning have shown unmatched performance on various ta...

4 Evgenii Zheltonozhskii, et al. ∙

∙ 11/17/2019

Smoothed Inference for Adversarially-Trained Models

Deep neural networks are known to be vulnerable to inputs with malicious...

0 Yaniv Nemcovsky, et al. ∙

∙ 11/17/2019

Loss Aware Post-training Quantization

Neural network quantization enables the deployment of large models on re...

0 Yury Nahshan, et al. ∙

∙ 09/25/2019

CAT: Compression-Aware Training for bandwidth reduction

Convolutional neural networks (CNNs) have become the dominant neural net...

0 Chaim Baskin, et al. ∙

∙ 05/26/2019

Feature Map Transform Coding for Energy-Efficient CNN Inference

Convolutional neural networks (CNNs) achieve state-of-the-art accuracy i...

0 Brian Chmiel, et al. ∙

∙ 04/22/2019

Towards Learning of Filter-Level Heterogeneous Compression of Convolutional Neural Networks

Recently, deep learning has become a de facto standard in machine learni...

0 Yochai Zur, et al. ∙

∙ 09/29/2018

NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

Convolutional Neural Networks (CNN) are very popular in many fields incl...

0 Chaim Baskin, et al. ∙

∙ 04/29/2018

UNIQ: Uniform Noise Injection for non-uniform Quantization of neural networks

We present a novel method for training a neural network amenable to infe...

0 Chaim Baskin, et al. ∙

∙ 04/29/2018

UNIQ: Uniform Noise Injection for the Quantization of Neural Networks

We present a novel method for training deep neural network amenable to i...

0 Chaim Baskin, et al. ∙

∙ 07/31/2017

Streaming Architecture for Large-Scale Quantized Neural Networks on an FPGA-Based Dataflow Platform

Deep neural networks (DNNs) are used by different applications that are ...

0 Chaim Baskin, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world