Vlado Menkovski

130 papers A* 6A 1B 14C 10Misc 2Journal 73Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LOREN: Low Rank-Based Code-Rate Adaptation in Neural Receivers. CoRR Bram Van Bolderik, Vlado Menkovski, Sonia M. Heemstra de Groot, Manil Dev Gomony
2026	J	`jnl`	VADA-NF: Improved Data-Driven Simulation of Nanopore Sequencing. Mach. Learn. Simon Martinus Koop, Mohammad Mahdi Mehmanchi, Jonas Niederle, Marc Pagès-Gallego, Vlado Menkovski
2025	J	`jnl`	A simple contrastive embedding framework for low-resource fake news detection. Neural Comput. Appl. Iftitahu Ni'mah, Rini Wijayanti, Agung Santosa, Asril Jarin, Tri Sampurno, Mohammad Teduh Uliniansyah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2025	B	`conf`	Aspect-Based Few-Shot Learning. DS Tim van Engeland, Lu Yin, Vlado Menkovski
2025	A*	`conf`	Deep Neural Cellular Potts Models. ICML Koen Minartz, Tim D'Hondt, Leon Hillmann, Jörn Starruß, Lutz Brusch, Vlado Menkovski
2025	J	`jnl`	Deep Neural Cellular Potts Models. CoRR Koen Minartz, Tim D'Hondt, Leon Hillmann, Jörn Starruß, Lutz Brusch, Vlado Menkovski
2025	B	`conf`	Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale. DS Pol Timmer, Koen Minartz, Vlado Menkovski
2025	J	`jnl`	Equivariant Flow Matching for Symmetry-Breaking Bifurcation Problems. CoRR Fleur Hendriks, Ondrej Rokos, Martin Doskár, Marc G. D. Geers, Vlado Menkovski
2025	J	`jnl`	Flow Matching for Geometric Trajectory Simulation. CoRR Kiet Bennema ten Brinke, Koen Minartz, Vlado Menkovski
2025	J	`jnl`	Plasma State Monitoring and Disruption Characterization using Multimodal VAEs. CoRR Yoeri Poels, Alessandro Pau, Christian Donner, Giulio Romanelli, Olivier Sauter, Cristina Venturini, Vlado Menkovski, TCV Team, The WPTE team
2025	J	`jnl`	Robust Confinement State Classification with Uncertainty Quantification through Ensembled Data-Driven Methods. CoRR Yoeri Poels, Cristina Venturini, Alessandro Pau, Olivier Sauter, Vlado Menkovski, TCV Team, The WPTE team
2025	B	`conf`	Score Matching on Large Geometric Graphs for Cosmology Generation. DS Diana-Alexandra Onutu, Yue Zhao, Joaquin Vanschoren, Vlado Menkovski
2025	J	`jnl`	Score Matching on Large Geometric Graphs for Cosmology Generation. CoRR Diana-Alexandra Onutu, Yue Zhao, Joaquin Vanschoren, Vlado Menkovski
2025	J	`jnl`	Symmetry-Informed Graph Neural Networks for Carbon Dioxide Isotherm and Adsorption Prediction in Aluminum-Substituted Zeolites. CoRR Marko Petkovic, José Manuel Vicent-Luna, Eliza Beate Dinne, Vlado Menkovski, Sofía Calero
2025	J	`jnl`	Towards Fully Automated Molecular Simulations: Multi-Agent Framework for Simulation Setup and Force Field Extraction. CoRR Marko Petkovic, Vlado Menkovski, Sofía Calero
2024	J	`jnl`	Accelerating Simulation of Two-Phase Flows with Neural PDE Surrogates. CoRR Yoeri Poels, Koen Minartz, Harshit Bansal, Vlado Menkovski
2024	C	`conf`	Agile Design-Space Exploration of Dynamic Layer-Skipping in Neural Receivers. DSD Bram Van Bolderik, Souradip Sarkar, Vlado Menkovski, Sonia M. Heemstra de Groot, Manil Dev Gomony
2024	J	`jnl`	Aspect-Based Few-Shot Learning. CoRR Tim van Engeland, Lu Yin, Vlado Menkovski
2024	J	`jnl`	Description Generation Using Variational Auto-Encoders for Precursor microRNA. Entropy Marko Petkovic, Vlado Menkovski
2024	J	`jnl`	Efficient Probabilistic Modeling of Crystallization at Mesoscopic Scale. CoRR Pol Timmer, Koen Minartz, Vlado Menkovski
2024	—	`conf`	Equivariant Parameter Sharing for Porous Crystalline Materials. IDA (1) Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofía Calero
2024	J	`jnl`	Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites. CoRR Marko Petkovic, José Manuel Vicent-Luna, Vlado Menkovski, Sofía Calero
2024	C	`conf`	MEAN: Mixture-of-Experts Based Neural Receiver. VLSI-SoC Bram Van Bolderik, Vlado Menkovski, Sonia M. Heemstra de Groot, Manil Dev Gomony
2024	—	`conf`	Neural Langevin Dynamics: Towards Interpretable Neural Stochastic Differential Equations. NLDL Simon Martinus Koop, Mark A. Peletier, Jacobus Willem Portegies, Vlado Menkovski
2024	—	`conf`	Node Classification in Random Trees. IDA (1) Wouter W. L. Nuijten, Vlado Menkovski
2024	J	`jnl`	Similarity Equivariant Graph Neural Networks for Homogenization of Metamaterials. CoRR Fleur Hendriks, Vlado Menkovski, Martin Doskár, Marc G. D. Geers, Ondrej Rokos
2024	J	`jnl`	Topological degree as a discrete diagnostic for disentanglement, with applications to the ΔVAE. CoRR Mahefa Ratsisetraina Ravelonanosy, Vlado Menkovski, Jacobus W. Portegies
2024	—	`conf`	Topological degree as a discrete diagnostic for disentanglement, with applications to the ΔVAE⋆. DS (LB) Mahefa Ratsisetraina Ravelonanosy, Vlado Menkovski, Jacobus W. Portegies
2024	J	`jnl`	Understanding complex crowd dynamics with generative neural simulators. CoRR Koen Minartz, Fleur Hendriks, Simon Martinus Koop, Alessandro Corbetta, Vlado Menkovski
2024	—	`conf`	VADA: A Data-Driven Simulator for Nanopore Sequencing. DS (1) Jonas Niederle, Simon M. Koop, Marc Pagès-Gallego, Vlado Menkovski
2024	J	`jnl`	VADA: a Data-Driven Simulator for Nanopore Sequencing. CoRR Jonas Niederle, Simon M. Koop, Marc Pagès-Gallego, Vlado Menkovski
2023	J	`jnl`	Comparison of neural closure models for discretised PDEs. Comput. Math. Appl. Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
2023	J	`jnl`	Description Generation using Variational Auto-Encoders for precursor microRNA. CoRR Marko Petkovic, Vlado Menkovski
2023	A*	`conf`	Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	J	`jnl`	Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	—	`conf`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Equivariant Networks for Porous Crystalline Materials. CoRR Marko Petkovic, Pablo Romero-Marimon, Vlado Menkovski, Sofía Calero
2023	A*	`conf`	Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics. NeurIPS Koen Minartz, Yoeri Poels, Simon M. Koop, Vlado Menkovski
2023	J	`jnl`	Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics. CoRR Koen Minartz, Yoeri Poels, Simon M. Koop, Vlado Menkovski
2023	J	`jnl`	Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates. CoRR Yoeri Poels, Gijs Derks, Egbert Westerhof, Koen Minartz, Sven Wiesen, Vlado Menkovski
2023	J	`jnl`	KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering. CoRR Iftitahu Ni'mah, Samaneh Khoshrou, Vlado Menkovski, Mykola Pechenizkiy
2023	A*	`conf`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2023	—	`conf`	NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. ACL (1) Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2023	J	`jnl`	NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist. CoRR Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2023	J	`jnl`	Node classification in random trees. CoRR Wouter W. L. Nuijten, Vlado Menkovski
2023	B	`conf`	Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations. IDA Loek Tonnaer, Mike Holenderski, Vlado Menkovski
2023	J	`jnl`	Supervised learning of process discovery techniques using graph neural networks. Inf. Syst. Dominique Sommers, Vlado Menkovski, Dirk Fahland
2022	J	`jnl`	Comparison of neural closure models for discretised PDEs. CoRR Hugo Melchers, Daan Crommelin, Barry Koren, Vlado Menkovski, Benjamin Sanderse
2022	J	`jnl`	Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2022	—	`conf`	Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2022	J	`jnl`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2022	J	`jnl`	Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations. CoRR Simon M. Koop, Mark A. Peletier, Jacobus W. Portegies, Vlado Menkovski
2022	A*	`conf`	Quantifying and Learning Linear Symmetry-Based Disentanglement. ICML Loek Tonnaer, Luis Armando Pérez Rey, Vlado Menkovski, Mike Holenderski, Jim Portegies
2022	B	`conf`	Semantic-Based Few-Shot Classification by Psychometric Learning. IDA Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2022	B	`conf`	Simulation of Scientific Experiments with Generative Models. IDA Stepan Veretennikov, Koen Minartz, Vlado Menkovski, Burcu Gumuscu, Jan de Boer
2022	J	`jnl`	Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
2022	A	`conf`	Superposing many tickets into one: A performance booster for sparse neural network training. UAI Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
2022	J	`jnl`	Towards Learned Simulators for Cell Migration. CoRR Koen Minartz, Yoeri Poels, Vlado Menkovski
2022	B	`conf`	VAE-CE: Visual Contrastive Explanation Using Disentangled VAEs. IDA Yoeri Poels, Vlado Menkovski
2022	—	`conf`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2022	J	`jnl`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2021	J	`jnl`	Calibrated Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2021	J	`jnl`	Efficient and effective training of sparse recurrent neural networks. Neural Comput. Appl. Shiwei Liu, Iftitahu Ni'mah, Vlado Menkovski, Decebal Constantin Mocanu, Mykola Pechenizkiy
2021	C	`conf`	Hierarchical Semantic Segmentation using Psychometric Learning. ACML Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
2021	J	`jnl`	Hierarchical Semantic Segmentation using Psychometric Learning. CoRR Lu Yin, Vlado Menkovski, Shiwei Liu, Mykola Pechenizkiy
2021	J	`jnl`	Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	—	`conf`	On Generalization of Graph Autoencoders with Adversarial Training. ECML/PKDD (2) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	On Generalization of Graph Autoencoders with Adversarial Training. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	B	`conf`	Process Discovery Using Graph Neural Networks. ICPM Dominique Sommers, Vlado Menkovski, Dirk Fahland
2021	J	`jnl`	Process Discovery Using Graph Neural Networks. CoRR Dominique Sommers, Vlado Menkovski, Dirk Fahland
2021	—	`conf`	ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. EMNLP (Findings) Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection. CoRR Iftitahu Ni'mah, Meng Fang, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	Semantic-Based Few-Shot Learning by Interactive Psychometric Testing. CoRR Lu Yin, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2021	C	`conf`	Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning. ACML Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
2021	J	`jnl`	VAE-CE: Visual Contrastive Explanation using Disentangled VAEs. CoRR Yoeri Poels, Vlado Menkovski
2021	C	`conf`	calibrated adversarial training. ACML Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	A Metric for Linear Symmetry-Based Disentanglement. CoRR Luis A. Pérez Rey, Loek Tonnaer, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
2020	J	`jnl`	Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	Causal Discovery from Incomplete Data: A Deep Learning Approach. CoRR Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy
2020	—	`conf`	Complex Vehicle Routing with Memory Augmented Neural Networks. ICPS Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
2020	J	`jnl`	Complex Vehicle Routing with Memory Augmented Neural Networks. CoRR Marijn van Knippenberg, Mike Holenderski, Vlado Menkovski
2020	Misc	`conf`	Detection of Mild Dyspnea from Pairs of Speech Recordings. ICASSP Sander M. Boelders, Venkata Srikanth Nallanthighal, Vlado Menkovski, Aki Härmä
2020	A*	`conf`	Diffusion Variational Autoencoders. IJCAI Luis A. Pérez Rey, Vlado Menkovski, Jim Portegies
2020	B	`conf`	Evaluation of CNN Performance in Semantically Relevant Latent Spaces. IDA Jeroen van Doorenmalen, Vlado Menkovski
2020	J	`jnl`	Explaining Predictions by Approximating the Local Decision Boundary. CoRR Georgios Vlassopoulos, Tim van Erven, Henry Brighton, Vlado Menkovski
2020	—	`conf`	Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing. ECML/PKDD (2) Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
2020	J	`jnl`	Knowledge Elicitation using Deep Metric Learning and Psychometric Testing. CoRR Lu Yin, Vlado Menkovski, Mykola Pechenizkiy
2020	J	`jnl`	Pedestrian orientation dynamics from high-fidelity measurements. CoRR Joris Willems, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
2020	J	`jnl`	Quantifying and Learning Disentangled Representations with Limited Supervision. CoRR Loek Tonnaer, Luis A. Pérez Rey, Vlado Menkovski, Mike Holenderski, Jacobus W. Portegies
2019	B	`conf`	Anomaly Detection for Visual Quality Control of 3D-Printed Products. IJCNN Loek Tonnaer, Jiapeng Li, Vladimir Osin, Mike Holenderski, Vlado Menkovski
2019	J	`jnl`	BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation. CoRR Iftitahu Ni'mah, Vlado Menkovski, Mykola Pechenizkiy
2019	J	`jnl`	Deep learning velocity signals allows to quantify turbulence intensity. CoRR Alessandro Corbetta, Vlado Menkovski, Roberto Benzi, Federico Toschi
2019	J	`jnl`	Diffusion Variational Autoencoders. CoRR Luis A. Pérez Rey, Vlado Menkovski, Jacobus W. Portegies
2019	J	`jnl`	Evolutionary Construction of Convolutional Neural Networks. CoRR Marijn van Knippenberg, Vlado Menkovski, Sergio Consoli
2019	—	`conf`	Extended 2D Scene Image-Based 3D Scene Retrieval. 3DOR@Eurographics 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
2019	J	`jnl`	Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning. CoRR Niels Hellinga, Vlado Menkovski
2019	B	`conf`	Micro-expression detection in long videos using optical flow and recurrent neural networks. FG Michiel Verburg, Vlado Menkovski
2019	J	`jnl`	Micro-expression detection in long videos using optical flow and recurrent neural networks. CoRR Michiel Verburg, Vlado Menkovski
2019	J	`jnl`	StampNet: unsupervised multi-class object discovery. CoRR Joost Visser, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
2019	B	`conf`	Stampnet: Unsupervised Multi-Class Object Discovery. ICIP Joost Visser, Alessandro Corbetta, Vlado Menkovski, Federico Toschi
2019	—	`ch.`	The Role of Deep Learning in Improving Healthcare. Data Science for Healthcare Stefan Thaler, Vlado Menkovski
2019	—	`conf`	VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance. VTC Spring Yuhao Wang, Vlado Menkovski, Ivan Wang Hei Ho, Mykola Pechenizkiy
2018	J	`jnl`	Anomaly Detection for imbalanced datasets with Deep Generative Models. CoRR Nazly Rocio Santos Buitrago, Loek Tonnaer, Vlado Menkovski, Dimitrios Mavroeidis
2018	J	`jnl`	Deep Learning in Information Security. CoRR Stefan Thaler, Vlado Menkovski, Milan Petkovic
2018	—	`conf`	Deep Metric Learning for Sequential Data Using Approximate Information. MLDM (1) Stefan Thaler, Vlado Menkovski, Milan Petkovic
2018	—	`conf`	Evolutionary Construction of Convolutional Neural Networks. LOD Marijn van Knippenberg, Vlado Menkovski, Sergio Consoli
2018	B	`conf`	Shunting Trains with Deep Reinforcement Learning. SMC Evertjan Peer, Vlado Menkovski, Yingqian Zhang, Wan-Jui Lee
2018	—	`conf`	Understanding anatomy classification through attentive response maps. ISBI Devinder Kumar, Vlado Menkovski, Graham W. Taylor, Alexander Wong
2017	—	`conf`	Unsupervised Signature Extraction from Forensic Logs. ECML/PKDD (3) Stefan Thaler, Vlado Menkovski, Milan Petkovic
2017	B	`conf`	Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields. AVSS Alessandro Corbetta, Vlado Menkovski, Federico Toschi
2017	J	`jnl`	Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields. CoRR Alessandro Corbetta, Vlado Menkovski, Federico Toschi
2016	J	`jnl`	Understanding Anatomy Classification Through Visualization. CoRR Devinder Kumar, Vlado Menkovski
2015	J	`jnl`	Can Pretrained Neural Networks Detect Anatomy? CoRR Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch
2015	—	`book`	Computational Inference and Control of Quality in Multimedia Services Vlado Menkovski
2015	J	`jnl`	Network analysis on Skype end-to-end video quality. Int. J. Pervasive Comput. Commun. George Exarchakos, Luca Druda, Vlado Menkovski, Antonio Liotta
2013	C	`conf`	Instantaneous Video Quality Assessment for lightweight devices. MoMM Antonio Liotta, Decebal Constantin Mocanu, Vlado Menkovski, Luciana Cagnetta, Georgios Exarchakos
2013	C	`conf`	Intelligent control for adaptive video streaming. ICCE Vlado Menkovski, Antonio Liotta
2013	J	`jnl`	Skype Resilience to High Motion Videos. Int. J. Wavelets Multiresolution Inf. Process. George Exarchakos, Luca Druda, Vlado Menkovski, Paolo Bellavista, Antonio Liotta
2012	J	`jnl`	Adaptive psychometric scaling for video quality assessment. Signal Process. Image Commun. Vlado Menkovski, Antonio Liotta
2012	C	`conf`	Quality of experience management for video streams: the case of Skype. MoMM Antonio Liotta, Luca Druda, Vlado Menkovski, Georgios Exarchakos
2012	Misc	`conf`	Video quality degradation on IPTV networks. ICNC Jewel Okyere-Benya, Mamoon Aldiabat, Vlado Menkovski, George Exarchakos, Antonio Liotta
2011	C	`conf`	Can Skype be used beyond video calling? MoMM Georgios Exarchakos, Vlado Menkovski, Antonio Liotta
2011	—	`conf`	Tackling the Sheer Scale of Subjective QoE. MobiMedia Vlado Menkovski, Georgios Exarchakos, Antonio Liotta
2011	J	`jnl`	The Value of Relative Quality in Video Delivery. J. Mobile Multimedia Vlado Menkovski, Georgios Exarchakos, Antonio Liotta
2010	—	`conf`	Machine Learning Approach for Quality of Experience Aware Networks. INCoS Vlado Menkovski, Georgios Exarchakos, Antonio Liotta
2010	J	`jnl`	Quality of Experience Models for Multimedia Streaming. Int. J. Mob. Comput. Multim. Commun. Vlado Menkovski, Georgios Exarchakos, Antonio Liotta, Antonio Cuadra Sánchez
2009	C	`conf`	Predicting quality of experience in multimedia streaming. MoMM Vlado Menkovski, Adetola Oredope, Antonio Liotta, Antonio Cuadra Sánchez
2008	—	`conf`	AI Model for Computer games based on Case Based Reasoning and AI Planning. DIMEA Vlado Menkovski, Dimitrios Metafas