Elena Mocanu

Elena Mocanu

Universiteit Twente

H-index: 20

Europe-Netherlands

About Elena Mocanu

Elena Mocanu, With an exceptional h-index of 20 and a recent h-index of 17 (since 2020), a distinguished researcher at Universiteit Twente, specializes in the field of Machine Learning, Sparse Neural Networks.

His recent articles reflect a diverse array of research interests and contributions to the field:

Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning

Enhancing Learning in Sparse Neural Networks: A Hebbian Learning Approach

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

Towards Implementing Truly Sparse Connections in Deep RL Agents

Dynamic Sparse Training for Deep Reinforcement Learning

The mutually reinforcing of sparse data and sparse training models

Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders

Elena Mocanu Information

University

Position

Assistant Professor

Citations(all)

2732

Citations(since 2020)

2414

Cited By

1193

hIndex(all)

20

hIndex(since 2020)

17

i10Index(all)

26

i10Index(since 2020)

24

Email

University Profile Page

Google Scholar

Elena Mocanu Skills & Research Interests

Machine Learning

Sparse Neural Networks

Top articles of Elena Mocanu

Title

Journal

Author(s)

Publication Date

Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning

arXiv preprint arXiv:2302.06548

Bram Grooten

Ghada Sokar

Shibhansh Dohare

Elena Mocanu

Matthew E Taylor

...

2023/2/13

Enhancing Learning in Sparse Neural Networks: A Hebbian Learning Approach

Alexander de Ranitz

Ardion D Beldad

Elena Mocanu

2023

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation

arXiv preprint arXiv:2312.04727

Boqian Wu

Qiao Xiao

Shiwei Liu

Lu Yin

Mykola Pechenizkiy

...

2023/12/7

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

ICLR2022, The International Conference on Learning Representations

Shiwei Liu

Tianlong Chen

Zahra Atashgahi

Xiaohan Chen

Ghada Sokar

...

2021/6/28

Towards Implementing Truly Sparse Connections in Deep RL Agents

Bram J Grooten

Ghada Sokar

Elena Mocanu

Shibhansh Dohare

Matthew E Taylor

...

2022/7/13

Dynamic Sparse Training for Deep Reinforcement Learning

IJCAI-ECAI 2022 (best paper award at ALA 2022), 31st International Joint Conference on Artificial Intelligence, arXiv preprint arXiv:2106.04217

Ghada Sokar

Elena Mocanu

Decebal Constantin Mocanu

Mykola Pechenizkiy

Peter Stone

2022/7

The mutually reinforcing of sparse data and sparse training models

Işıl Baysal Erez

Elena Mocanu

Maurice van Keulen

2022/4/28

Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders

Machine Learning Journal (ECML-PKDD 2022 journal track)

Zahra Atashgahi

Ghada Sokar

Tim van der Lee

Elena Mocanu

Decebal Constantin Mocanu

...

2021/10/27

Dynamic Sparse Network for Time Series Classification: Learning What to" see''

Qiao Xiao

Boqian Wu

Yu Zhang

Shiwei Liu

Mykola Pechenizkiy

...

2022/11

Sparse Training Theory for Scalable and Efficient Agents

arXiv preprint arXiv:2103.01636

Decebal Constantin Mocanu

Elena Mocanu

Tiago Pinto

Selima Curci

Phuong H Nguyen

...

2021/3/2

Forecasting

Encyclopedia of Operations Research and Management Science, Forthcoming

Andreas Graefe

Kesten C Green

J Scott Armstrong

2011/9/16

Effectiveness of neural language models for word prediction of textual mammography reports

Mihai David Marin

Elena Mocanu

Christin Seifert

2020/10/11

See List of Professors in Elena Mocanu University(Universiteit Twente)

Co-Authors

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