Vlado Menkovski

Orcid: 0000-0001-5262-0605

According to our database1, Vlado Menkovski authored at least 79 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites.
CoRR, 2024

Neural Langevin Dynamics: Towards Interpretable Neural Stochastic Differential Equations.
Proceedings of the Northern Lights Deep Learning Conference, 2024

2023
Supervised learning of process discovery techniques using graph neural networks.
Inf. Syst., May, 2023

Description Generation using Variational Auto-Encoders for precursor microRNA.
CoRR, 2023

Node classification in random trees.
CoRR, 2023

KeyGen2Vec: Learning Document Embedding via Multi-label Keyword Generation in Question-Answering.
CoRR, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.
CoRR, 2023

Fast Dynamic 1D Simulation of Divertor Plasmas with Neural PDE Surrogates.
CoRR, 2023

Equivariant Networks for Porous Crystalline Materials.
CoRR, 2023

Comparison of neural closure models for discretised PDEs.
Comput. Math. Appl., 2023

Enhancing Adversarial Training via Reweighting Optimization Trajectory.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Out-of-Distribution Generalisation with Symmetry-Based Disentangled Representations.
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Direction-aggregated Attack for Transferable Adversarial Examples.
ACM J. Emerg. Technol. Comput. Syst., 2022

Towards Learned Simulators for Cell Migration.
CoRR, 2022

Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training.
CoRR, 2022

Superposing many tickets into one: A performance booster for sparse neural network training.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets.
Proceedings of the Learning on Graphs Conference, 2022

Semantic-Based Few-Shot Classification by Psychometric Learning.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Simulation of Scientific Experiments with Generative Models.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

VAE-CE: Visual Contrastive Explanation Using Disentangled VAEs.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Quantifying and Learning Linear Symmetry-Based Disentanglement.
Proceedings of the International Conference on Machine Learning, 2022

2021
Efficient and effective training of sparse recurrent neural networks.
Neural Comput. Appl., 2021

Semantic-Based Few-Shot Learning by Interactive Psychometric Testing.
CoRR, 2021

On Generalization of Graph Autoencoders with Adversarial Training.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Process Discovery Using Graph Neural Networks.
Proceedings of the 3rd International Conference on Process Mining, 2021

ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Hierarchical Semantic Segmentation using Psychometric Learning.
Proceedings of the Asian Conference on Machine Learning, 2021

Time-Constrained Multi-Agent Path Finding in Non-Lattice Graphs with Deep Reinforcement Learning.
Proceedings of the Asian Conference on Machine Learning, 2021

calibrated adversarial training.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
A Metric for Linear Symmetry-Based Disentanglement.
CoRR, 2020

Quantifying and Learning Disentangled Representations with Limited Supervision.
CoRR, 2020

Bridging the Performance Gap between FGSM and PGD Adversarial Training.
CoRR, 2020

Explaining Predictions by Approximating the Local Decision Boundary.
CoRR, 2020

Causal Discovery from Incomplete Data: A Deep Learning Approach.
CoRR, 2020

Pedestrian orientation dynamics from high-fidelity measurements.
CoRR, 2020

Knowledge Elicitation Using Deep Metric Learning and Psychometric Testing.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Diffusion Variational Autoencoders.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Evaluation of CNN Performance in Semantically Relevant Latent Spaces.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Complex Vehicle Routing with Memory Augmented Neural Networks.
Proceedings of the IEEE Conference on Industrial Cyberphysical Systems, 2020

Detection of Mild Dyspnea from Pairs of Speech Recordings.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Deep learning velocity signals allows to quantify turbulence intensity.
CoRR, 2019

BSDAR: Beam Search Decoding with Attention Reward in Neural Keyphrase Generation.
CoRR, 2019

Hierarchical Annotation of Images with Two-Alternative-Forced-Choice Metric Learning.
CoRR, 2019

VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance.
Proceedings of the 89th IEEE Vehicular Technology Conference, 2019

Anomaly Detection for Visual Quality Control of 3D-Printed Products.
Proceedings of the International Joint Conference on Neural Networks, 2019

Stampnet: Unsupervised Multi-Class Object Discovery.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Micro-expression detection in long videos using optical flow and recurrent neural networks.
Proceedings of the 14th IEEE International Conference on Automatic Face & Gesture Recognition, 2019


The Role of Deep Learning in Improving Healthcare.
Proceedings of the Data Science for Healthcare - Methodologies and Applications, 2019

2018
Anomaly Detection for imbalanced datasets with Deep Generative Models.
CoRR, 2018

Deep Learning in Information Security.
CoRR, 2018

Shunting Trains with Deep Reinforcement Learning.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Evolutionary Construction of Convolutional Neural Networks.
Proceedings of the Machine Learning, Optimization, and Data Science, 2018

Deep Metric Learning for Sequential Data Using Approximate Information.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2018

Understanding anatomy classification through attentive response maps.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Unsupervised Signature Extraction from Forensic Logs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields.
Proceedings of the 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2017

2016
Understanding Anatomy Classification Through Visualization.
CoRR, 2016

2015
Network analysis on Skype end-to-end video quality.
Int. J. Pervasive Comput. Commun., 2015

Can Pretrained Neural Networks Detect Anatomy?
CoRR, 2015

Computational Inference and Control of Quality in Multimedia Services
Springer, ISBN: 978-3-319-24792-2, 2015

2013
Skype Resilience to High Motion Videos.
Int. J. Wavelets Multiresolution Inf. Process., 2013

Instantaneous Video Quality Assessment for lightweight devices.
Proceedings of the 11th International Conference on Advances in Mobile Computing & Multimedia, 2013

Intelligent control for adaptive video streaming.
Proceedings of the IEEE International Conference on Consumer Electronics, 2013

2012
Adaptive psychometric scaling for video quality assessment.
Signal Process. Image Commun., 2012

Quality of experience management for video streams: the case of Skype.
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia, 2012

Video quality degradation on IPTV networks.
Proceedings of the International Conference on Computing, Networking and Communications, 2012

2011
The Value of Relative Quality in Video Delivery.
J. Mobile Multimedia, 2011

Can Skype be used beyond video calling?
Proceedings of the MoMM'2011, 2011

Tackling the Sheer Scale of Subjective QoE.
Proceedings of the Mobile Multimedia Communications - 7th International ICST Conference, 2011

2010
Quality of Experience Models for Multimedia Streaming.
Int. J. Mob. Comput. Multim. Commun., 2010

Machine Learning Approach for Quality of Experience Aware Networks.
Proceedings of the 2nd International Conference on Intelligent Networking and Collaborative Systems, 2010

2009
Predicting quality of experience in multimedia streaming.
Proceedings of the MoMM'2009, 2009

2008
AI Model for Computer games based on Case Based Reasoning and AI Planning.
Proceedings of the Third International Conference on Digital Interactive Media in Entertainment and Arts, 2008


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