Andreas Loukas

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 75

Top Venues

CoRR

NeurIPS

ICML

IEEE Trans. Signal Process.

Delft University of Technology, Netherlands (PHD)

Education History

Delft University of Technology, Netherlands

PHD

Publications

Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
Protein Discovery with Discrete Walk-Jump Sampling. ICLR (2024)
Natasa Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient. CoRR (2024)
Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani
Towards Understanding and Improving GFlowNet Training. CoRR (2023)
Karolis Martinkus, Jan Ludwiczak, Kyunghyun Cho, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas
AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies. CoRR (2023)
Andreas Loukas, Pan Kessel
Batched Predictors Generalize within Distribution. CoRR (2023)
Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas
AbDiffuser: full-atom generation of in-vitro functioning antibodies. NeurIPS (2023)
Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi
Protein Discovery with Discrete Walk-Jump Sampling. CoRR (2023)
Mattia Atzeni, Mrinmaya Sachan, Andreas Loukas
Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning. CoRR (2023)
Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani
Towards Understanding and Improving GFlowNet Training. ICML (2023)
Mattia Atzeni, Mrinmaya Sachan, Andreas Loukas
Infusing Lattice Symmetry Priors in Attention Mechanisms for Sample-Efficient Abstract Geometric Reasoning. ICML (2023)
Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. NeurIPS (2022)
Nikolaos Karalias, Joshua Robinson, Andreas Loukas, Stefanie Jegelka
Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. CoRR (2022)
Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer
SPECTRE : Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators. CoRR (2022)
Karolis Martinkus, Andreas Loukas, Nathanaël Perraudin, Roger Wattenhofer
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators. ICML (2022)
Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
On the generalization of learning algorithms that do not converge. CoRR (2022)
Max W. Shen, Ehsan Hajiramezanali, Gabriele Scalia, Alex Tseng, Nathaniel Diamant, Tommaso Biancalani, Andreas Loukas
Conditional Diffusion with Less Explicit Guidance via Model Predictive Control. CoRR (2022)
Andreas Scheck, Stéphane Rosset, Michaël Defferrard, Andreas Loukas, Jaume Bonet, Pierre Vandergheynst, Bruno E. Correia
RosettaSurf - A surface-centric computational design approach. PLoS Comput. Biol. 18 (3) (2022)
Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
On the generalization of learning algorithms that do not converge. NeurIPS (2022)
Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hötzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences. CoRR (2022)
Mattia Atzeni, Jasmina Bogojeska, Andreas Loukas
SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning. NeurIPS (2021)
Andreas Loukas, Marinos Poiitis, Stefanie Jegelka
What training reveals about neural network complexity. NeurIPS (2021)
Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas
Attention is Not All You Need: Pure Attention Loses Rank Doubly Exponentially with Depth. CoRR (2021)
Andreas Loukas, Marinos Poiitis, Stefanie Jegelka
What training reveals about neural network complexity. CoRR (2021)
Mattia Atzeni, Jasmina Bogojeska, Andreas Loukas
SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning. CoRR (2021)
Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
Partition and Code: learning how to compress graphs. CoRR (2021)
Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
Partition and Code: learning how to compress graphs. NeurIPS (2021)
Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas
Attention is not all you need: pure attention loses rank doubly exponentially with depth. ICML (2021)
Chen Avin, Marcin Bienkowski, Andreas Loukas, Maciej Pacut, Stefan Schmid
Dynamic Balanced Graph Partitioning. SIAM J. Discret. Math. 34 (3) (2020)
Nikolaos Karalias, Andreas Loukas
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs. NeurIPS (2020)
Andreas Loukas
What graph neural networks cannot learn: depth vs width. ICLR (2020)
Nikolaos Karalias, Andreas Loukas
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs. CoRR (2020)
Yu Jin, Andreas Loukas, Joseph F. JáJá
Graph Coarsening with Preserved Spectral Properties. AISTATS (2020)
Clément Vignac, Andreas Loukas, Pascal Frossard
Building powerful and equivariant graph neural networks with message-passing. CoRR (2020)
Clément Vignac, Andreas Loukas, Pascal Frossard
Building powerful and equivariant graph neural networks with structural message-passing. NeurIPS (2020)
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi
Multi-Head Attention: Collaborate Instead of Concatenate. CoRR (2020)
Andreas Loukas
How hard is to distinguish graphs with graph neural networks? NeurIPS (2020)
Andreas Loukas
How hard is graph isomorphism for graph neural networks? CoRR (2020)
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi
On the Relationship between Self-Attention and Convolutional Layers. ICLR (2020)
Konstantinos Pitas, Andreas Loukas, Mike Davies, Pierre Vandergheynst
Some limitations of norm based generalization bounds in deep neural networks. CoRR (2019)
Andreas Loukas
Graph Reduction with Spectral and Cut Guarantees. J. Mach. Learn. Res. 20 (2019)
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi
On the Relationship between Self-Attention and Convolutional Layers. CoRR (2019)
Nicolas Tremblay, Andreas Loukas
Approximating Spectral Clustering via Sampling: a Review. CoRR (2019)
Jean-Baptiste Cordonnier, Andreas Loukas
Extrapolating paths with graph neural networks. CoRR (2019)
Elvin Isufi, Andreas Loukas, Nathanaël Perraudin, Geert Leus
Forecasting Time Series With VARMA Recursions on Graphs. IEEE Trans. Signal Process. 67 (18) (2019)
Andreas Loukas
What graph neural networks cannot learn: depth vs width. CoRR (2019)
Andreas Loukas, Nathanaël Perraudin
Stationary time-vertex signal processing. EURASIP J. Adv. Signal Process. 2019 (2019)
Younjoo Seo, Andreas Loukas, Nathanaël Perraudin
Discriminative structural graph classification. CoRR (2019)
Jean-Baptiste Cordonnier, Andreas Loukas
Extrapolating Paths with Graph Neural Networks. IJCAI (2019)
Andreas Loukas, Pierre Vandergheynst
Spectrally approximating large graphs with smaller graphs. CoRR (2018)
Elvin Isufi, Andreas Loukas, Nathanaël Perraudin, Geert Leus
Forecasting Time Series with VARMA Recursions on Graphs. CoRR (2018)
Lionel Martin, Andreas Loukas, Pierre Vandergheynst
Fast Approximate Spectral Clustering for Dynamic Networks. ICML (2018)
Andreas Loukas, Pierre Vandergheynst
Spectrally Approximating Large Graphs with Smaller Graphs. ICML (2018)
Andreas Loukas
Graph reduction by local variation. CoRR (2018)
Francesco Grassi, Andreas Loukas, Nathanaël Perraudin, Benjamin Ricaud
A Time-Vertex Signal Processing Framework: Scalable Processing and Meaningful Representations for Time-Series on Graphs. IEEE Trans. Signal Process. 66 (3) (2018)
Chen Avin, Alexandr Hercules, Andreas Loukas, Stefan Schmid
: Toward robust demand-aware network designs. Inf. Process. Lett. 133 (2018)
Andreas Loukas, Elvin Isufi, Nathanaël Perraudin
Predicting the evolution of stationary graph signals. ACSSC (2017)
Elvin Isufi, Andreas Loukas, Andrea Simonetto, Geert Leus
Filtering Random Graph Processes Over Random Time-Varying Graphs. IEEE Trans. Signal Process. 65 (16) (2017)
Francesco Grassi, Andreas Loukas, Nathanaël Perraudin, Benjamin Ricaud
A Time-Vertex Signal Processing Framework. CoRR (2017)
Andreas Loukas
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices? ICML (2017)
Nathanaël Perraudin, Andreas Loukas, Francesco Grassi, Pierre Vandergheynst
Towards stationary time-vertex signal processing. ICASSP (2017)
Elvin Isufi, Andreas Loukas, Andrea Simonetto, Geert Leus
Autoregressive Moving Average Graph Filtering. IEEE Trans. Signal Process. 65 (2) (2017)
Elvin Isufi, Andreas Loukas, Andrea Simonetto, Geert Leus
Filtering Random Graph Processes Over Random Time-Varying Graphs. CoRR (2017)
Claudio Martella, Dionysios Logothetis, Andreas Loukas, Georgos Siganos
Spinner: Scalable Graph Partitioning in the Cloud. ICDE (2017)
Elvin Isufi, Andreas Loukas, Geert Leus
Autoregressive moving average graph filters a stable distributed implementation. ICASSP (2017)
Vassilis Kalofolias, Andreas Loukas, Dorina Thanou, Pascal Frossard
Learning time varying graphs. ICASSP (2017)
Chen Avin, Alexandr Hercules, Andreas Loukas, Stefan Schmid
Towards Communication-Aware Robust Topologies. CoRR (2017)
Marco Cattani, Andreas Loukas, Marco Zimmerling, Marco Zuniga, Koen Langendoen
Staffetta: Smart Duty-Cycling for Opportunistic Data Collection. SenSys (2016)
Andreas Loukas, Damien Foucard
Frequency analysis of time-varying graph signals. GlobalSIP (2016)
Andreas Loukas, Damien Foucard
Frequency Analysis of Temporal Graph Signals. CoRR (2016)
Andreas Loukas, Nathanaël Perraudin
Stationary time-vertex signal processing. CoRR (2016)
Chen Avin, Andreas Loukas, Maciej Pacut, Stefan Schmid
Online Balanced Repartitioning. DISC (2016)
Nathanaël Perraudin, Andreas Loukas, Francesco Grassi, Pierre Vandergheynst
Towards stationary time-vertex signal processing. CoRR (2016)
Elvin Isufi, Andreas Loukas, Andrea Simonetto, Geert Leus
Separable autoregressive moving average graph-temporal filters. EUSIPCO (2016)
Elvin Isufi, Andreas Loukas, Andrea Simonetto, Geert Leus
Distributed Time-Varying Graph Filtering. CoRR (2016)
Andreas Loukas, Nathanaël Perraudin
Predicting the evolution of stationary graph signals. CoRR (2016)
Andreas Loukas, Andrea Simonetto, Geert Leus
Distributed Autoregressive Moving Average Graph Filters. CoRR (2015)
Andreas Loukas, Marco Cattani, Marco Zuniga, Jie Gao
Graph scale-space theory for distributed peak and pit identification. IPSN (2015)
Chen Avin, Andreas Loukas, Maciej Pacut, Stefan Schmid
Online Balanced Repartitioning. CoRR (2015)
Andreas Loukas, Andrea Simonetto, Geert Leus
Distributed Autoregressive Moving Average Graph Filters. IEEE Signal Process. Lett. 22 (11) (2015)
Elvin Isufi, Andrea Simonetto, Andreas Loukas, Geert Leus
Stochastic graph filtering on time-varying graphs. CAMSAP (2015)
Andreas Loukas, Marco Zuniga, Ioannis Protonotarios, Jie Gao
How to identify global trends from local decisions? Event region detection on mobile networks. INFOCOM (2014)
Yunus Durmus, Andreas Loukas, Ertan Onur, Koen Langendoen
Sybil-Resistant Meta Strategies for the Forwarder's Dilemma. SASO (2014)
Marco Cattani, Marco Zuniga, Andreas Loukas, Koen Langendoen
Lightweight neighborhood cardinality estimation in dynamic wireless networks. IPSN (2014)
Andreas Loukas, Marco Zuniga, Matthias Woehrle, Marco Cattani, Koen Langendoen
Think globally, act locally: on the reshaping of information landscapes. IPSN (2013)
Andreas Loukas, Matthias Woehrle, Marco Zuniga, Koen Langendoen
Fairness for All, Rate Allocation for Mobile Wireless Networks. MASS (2013)
Andreas Loukas, Matthias Woehrle, Philipp M. Glatz, Koen Langendoen
On distributed computation of information potentials. FOMC (2012)
Andreas Loukas, Matthias Woehrle, Koen Langendoen
On mining sensor network software repositories. SESENA@ICSE (2011)
Orestis Akribopoulos, Dimitrios Bousis, Dionysios Efstathiou, Haris Koutsouridis, Marios Logaras, Andreas Loukas, Alexandros Nafas, Georgios Oikonomou, Irini Thireou, Nikos Vasilakis, Panagiotis C. Kokkinos, Georgios Mylonas, Ioannis Chatzigiannakis
A software platform for developing multi-player pervasive games using small programmable object technologies. MASS (2008)

Andreas Loukas.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Andreas Loukas