Vlado Menkovski

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 90

Top Venues

Publications

Yoeri Poels, Koen Minartz, Harshit Bansal, Vlado Menkovski
Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates. CoRR (2024)
Simon Martinus Koop, Mark A. Peletier, Jacobus Willem Portegies, Vlado Menkovski
Neural Langevin Dynamics: Towards Interpretable Neural Stochastic Differential Equations. NLDL (2024)
Wouter W. L. Nuijten, Vlado Menkovski
Node Classification in Random Trees. IDA (1) (2024)
Pol Timmer, Koen Minartz, Vlado Menkovski
Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale. CoRR (2024)
Marko Petkovic, José Manuel Vicent-Luna, Vlado Menkovski, Sofía Calero
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites. CoRR (2024)
Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofía Calero
Equivariant Parameter Sharing for Porous Crystalline Materials. IDA (1) (2024)
Fleur Hendriks, Vlado Menkovski, Martin Doskár, Marc G. D. Geers, Ondrej Rokos
Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials. CoRR (2024)
Jonas Niederle, Simon M. Koop, Marc Pagès-Gallego, Vlado Menkovski
VADA: a Data-Driven Simulator for Nanopore Sequencing. CoRR (2024)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) (2023)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. ACL (1) (2023)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR (2023)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR (2023)
Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
Comparison of neural closure models for discretised PDEs. Comput. Math. Appl. 143 (2023)
Loek Tonnaer, Mike Holenderski, Vlado Menkovski
Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations. IDA (2023)
Yoeri Poels, Gijs Derks, Egbert Westerhof, Koen Minartz, Sven Wiesen, Vlado Menkovski
Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates. CoRR (2023)
Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofía Calero
Equivariant Networks for Porous Crystalline Materials. CoRR (2023)
Iftitahu Ni'mah, Samaneh Khoshrou, Vlado Menkovski, Mykola Pechenizkiy
KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering. CoRR (2023)
Wouter W. L. Nuijten, Vlado Menkovski
Node classification in random trees. CoRR (2023)
Dominique Sommers, Vlado Menkovski, Dirk Fahland
Supervised learning of process discovery techniques using graph neural networks. Inf. Syst. 115 (2023)
Koen Minartz, Yoeri Poels, Simon M. Koop, Vlado Menkovski
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics. CoRR (2023)
Marko Petkovic, Vlado Menkovski
Description Generation using Variational Auto-Encoders for precursor microRNA. CoRR (2023)
Koen Minartz, Yoeri Poels, Simon M. Koop, Vlado Menkovski
Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics. NeurIPS (2023)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. CoRR (2023)
Simon M. Koop, Mark A. Peletier, Jacobus W. Portegies, Vlado Menkovski
Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations. CoRR (2022)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR (2022)
Stepan Veretennikov, Koen Minartz, Vlado Menkovski, Burcu Gumuscu, Jan de Boer
Simulation of Scientific Experiments with Generative Models. IDA (2022)
Loek Tonnaer, Luis Armando Pérez Rey, Vlado Menkovski, Mike Holenderski, Jim Portegies
Quantifying and Learning Linear Symmetry-Based Disentanglement. ICML (2022)
Yoeri Poels, Vlado Menkovski
VAE-CE: Visual Contrastive Explanation Using Disentangled VAEs. IDA (2022)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. 18 (3) (2022)
Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Semantic-Based Few-Shot Classification by Psychometric Learning. IDA (2022)
Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
Comparison of neural closure models for discretised PDEs. CoRR (2022)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
Superposing many tickets into one: A performance booster for sparse neural network training. UAI (2022)
Koen Minartz, Yoeri Poels, Vlado Menkovski
Towards Learned Simulators for Cell Migration. CoRR (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR (2022)
Yoeri Poels, Vlado Menkovski
VAE-CE: Visual Contrastive Explanation using Disentangled VAEs. CoRR (2021)
Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
Hierarchical Semantic Segmentation using Psychometric Learning. ACML (2021)
Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
Hierarchical Semantic Segmentation using Psychometric Learning. CoRR (2021)
Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. CoRR (2021)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. EMNLP (Findings) (2021)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
On Generalization of Graph Autoencoders with Adversarial Training. CoRR (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR (2021)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Calibrated Adversarial Training. CoRR (2021)
Dominique Sommers, Vlado Menkovski, Dirk Fahland
Process Discovery Using Graph Neural Networks. CoRR (2021)
Dominique Sommers, Vlado Menkovski, Dirk Fahland
Process Discovery Using Graph Neural Networks. ICPM (2021)
Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. CoRR (2021)
Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning. ACML (2021)
Shiwei Liu, Iftitahu Ni'mah, Vlado Menkovski, Decebal Constantin Mocanu, Mykola Pechenizkiy
Efficient and effective training of sparse recurrent neural networks. Neural Comput. Appl. 33 (15) (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
On Generalization of Graph Autoencoders with Adversarial Training. ECML/PKDD (2) (2021)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
calibrated adversarial training. ACML (2021)
Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
Complex Vehicle Routing with Memory Augmented Neural Networks. CoRR (2020)
Jeroen van Doorenmalen, Vlado Menkovski
Evaluation of CNN Performance in Semantically Relevant Latent Spaces. IDA (2020)
Georgios Vlassopoulos, Tim van Erven, Henry Brighton, Vlado Menkovski
Explaining Predictions by Approximating the Local Decision Boundary. CoRR (2020)
Joris Willems, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
Pedestrian orientation dynamics from high-fidelity measurements. CoRR (2020)
Loek Tonnaer, Luis A. Pérez Rey, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
Quantifying and Learning Disentangled Representations with Limited Supervision. CoRR (2020)
Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. ECML/PKDD (2) (2020)
Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy
Causal Discovery from Incomplete Data: A Deep Learning Approach. CoRR (2020)
Sander Boelders, Venkata Srikanth Nallanthighal, Vlado Menkovski, Aki Härmä
Detection of Mild Dyspnea from Pairs of Speech Recordings. ICASSP (2020)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR (2020)
Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. CoRR (2020)
Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
Complex Vehicle Routing with Memory Augmented Neural Networks. ICPS (2020)
Luis A. Pérez Rey, Loek Tonnaer, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
A Metric for Linear Symmetry-Based Disentanglement. CoRR (2020)
Luis A. Pérez Rey, Vlado Menkovski, Jim Portegies
Diffusion Variational Autoencoders. IJCAI (2020)
Hameed Abdul-Rashid, Juefei Yuan, Bo Li, Yijuan Lu, Tobias Schreck, Ngoc-Minh Bui, Trong-Le Do, Mike Holenderski, Dmitri Jarnikov, Tu-Khiem Le, Vlado Menkovski, Khac-Tuan Nguyen, Thanh-An Nguyen, Vinh-Tiep Nguyen, Van-Tu Ninh, Luis A. Pérez Rey, Minh-Triet Tran, Tianyang Wang
Extended 2D Scene Image-Based 3D Scene Retrieval. 3DOR@Eurographics (2019)
Luis A. Pérez Rey, Vlado Menkovski, Jacobus W. Portegies
Diffusion Variational Autoencoders. CoRR (2019)
Alessandro Corbetta, Vlado Menkovski, Roberto Benzi, Federico Toschi
Deep learning velocity signals allows to quantify turbulence intensity. CoRR (2019)
Niels Hellinga, Vlado Menkovski
Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning. CoRR (2019)
Yuhao Wang, Vlado Menkovski, Ivan Wang Hei Ho, Mykola Pechenizkiy
VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance. VTC Spring (2019)
Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy
BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation. CoRR (2019)
Loek Tonnaer, Jiapeng Li, Vladimir Osin, Mike Holenderski, Vlado Menkovski
Anomaly Detection for Visual Quality Control of 3D-Printed Products. IJCNN (2019)
Joost Visser, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
Stampnet: Unsupervised Multi-Class Object Discovery. ICIP (2019)
Marijn van Knippenberg, Vlado Menkovski, Sergio Consoli
Evolutionary Construction of Convolutional Neural Networks. CoRR (2019)
Michiel Verburg, Vlado Menkovski
Micro-expression detection in long videos using optical flow and recurrent neural networks. FG (2019)
Michiel Verburg, Vlado Menkovski
Micro-expression detection in long videos using optical flow and recurrent neural networks. CoRR (2019)
Joost Visser, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
StampNet: unsupervised multi-class object discovery. CoRR (2019)
Marijn van Knippenberg, Vlado Menkovski, Sergio Consoli
Evolutionary Construction of Convolutional Neural Networks. LOD (2018)
Nazly Rocio Santos Buitrago, Loek Tonnaer, Vlado Menkovski, Dimitrios Mavroeidis
Anomaly Detection for imbalanced datasets with Deep Generative Models. CoRR (2018)
Stefan Thaler, Vlado Menkovski, Milan Petkovic
Deep Metric Learning for Sequential Data Using Approximate Information. MLDM (1) (2018)
Stefan Thaler, Vlado Menkovski, Milan Petkovic
Deep Learning in Information Security. CoRR (2018)
Evertjan Peer, Vlado Menkovski, Yingqian Zhang, Wan-Jui Lee
Shunting Trains with Deep Reinforcement Learning. SMC (2018)
Devinder Kumar, Vlado Menkovski, Graham W. Taylor, Alexander Wong
Understanding anatomy classification through attentive response maps. ISBI (2018)
Stefan Thaler, Vlado Menkovski, Milan Petkovic
Unsupervised Signature Extraction from Forensic Logs. ECML/PKDD (3) (2017)
Alessandro Corbetta, Vlado Menkovski, Federico Toschi
Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields. AVSS (2017)
Alessandro Corbetta, Vlado Menkovski, Federico Toschi
Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields. CoRR (2017)
Devinder Kumar, Vlado Menkovski
Understanding Anatomy Classification Through Visualization. CoRR (2016)
Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch
Can Pretrained Neural Networks Detect Anatomy? CoRR (2015)
George Exarchakos, Luca Druda, Vlado Menkovski, Antonio Liotta
Network analysis on Skype end-to-end video quality. Int. J. Pervasive Comput. Commun. 11 (1) (2015)
Vlado Menkovski, Antonio Liotta
Intelligent control for adaptive video streaming. ICCE (2013)
Antonio Liotta, Decebal Constantin Mocanu, Vlado Menkovski, Luciana Cagnetta, Georgios Exarchakos
Instantaneous Video Quality Assessment for lightweight devices. MoMM (2013)
George Exarchakos, Luca Druda, Vlado Menkovski, Paolo Bellavista, Antonio Liotta
Skype Resilience to High Motion Videos. Int. J. Wavelets Multiresolution Inf. Process. 11 (3) (2013)
Jewel Okyere-Benya, Mamoon Aldiabat, Vlado Menkovski, George Exarchakos, Antonio Liotta
Video quality degradation on IPTV networks. ICNC (2012)
Vlado Menkovski, Antonio Liotta
Adaptive psychometric scaling for video quality assessment. Signal Process. Image Commun. 27 (8) (2012)
Antonio Liotta, Luca Druda, Vlado Menkovski, Georgios Exarchakos
Quality of experience management for video streams: the case of Skype. MoMM (2012)
Vlado Menkovski, Georgios Exarchakos, Antonio Liotta
Tackling the Sheer Scale of Subjective QoE. MobiMedia (2011)
Georgios Exarchakos, Vlado Menkovski, Antonio Liotta
Can Skype be used beyond video calling? MoMM (2011)

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Publication Activity (10 Years)

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Vlado Menkovski