Andreas Loukas

90 papers A* 23A 2B 2Misc 5Journal 48Unranked 9

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