7.1k citations
- L. Decin3 profiles131 · h 49
- C. Aerts3 profiles91 · h 67
- H. Sana3 profiles79 · h 44
- S. Poedts67 · h 46
- R. Keppens2 profiles63 · h 43
- H. Van Winckel2 profiles56 · h 15
- B. Vandenbussche3 profiles54 · h 45
- A. de Koter2 profiles50 · h 12
- T. Shenar47 · h 26
- P. Lagage37 · h 45
- D. Bowman33 · h 26
- G. Nelemans2 profiles33 · h 94
- Centre National de la Recherche ScientifiqueFR445 papers
- Institute of AstronomyRU425 papers
- Université Paris CitéFR224 papers
- Radboud University NijmegenNL210 papers
- Sorbonne UniversitéFR194 papers
- Université Paris-SaclayFR173 papers
- University of AmsterdamNL173 papers
- Max Planck Institute for AstronomyDE172 papers
- Royal Observatory of BelgiumBE161 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR159 papers
- Laboratoire d’études spatiales et d’instrumentation en astrophysiqueFR148 papers
- Leiden UniversityNL145 papers
5 papers · 2 filters
Practical applicability of deep neural networks for overlapping speaker separation
Pieter Appeltans, Jeroen Zegers, Hugo Van hamme
This paper examines the applicability in realistic scenarios of two deep learning based solutions to the overlapping speaker separation problem. Firstly, we present experiments tha…
CNN-LSTM models for Multi-Speaker Source Separation using Bayesian Hyper Parameter Optimization
Jeroen Zegers, Hugo Van hamme
In recent years there have been many deep learning approaches towards the multi-speaker source separation problem. Most use Long Short-Term Memory - Recurrent Neural Networks (LSTM…
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
Fanghui Liu, Xiaolin Huang, Yudong Chen +2
In this paper, we propose a fast surrogate leverage weighted sampling strategy to generate refined random Fourier features for kernel approximation. Compared to the current state-o…
Justifying Diagnosis Decisions by Deep Neural Networks
Graham Spinks, Marie-Francine Moens
An integrated approach is proposed across visual and textual data to both determine and justify a medical diagnosis by a neural network. As deep learning techniques improve, intere…
Discovering Episodes with Compact Minimal Windows
Nikolaj Tatti
Discovering the most interesting patterns is the key problem in the field of pattern mining. While ranking or selecting patterns is well-studied for itemsets it is surprisingly und…