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ORCIDSepp Hochreiter
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- affiliation: Johannes Kepler University of Linz, Austria
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2020 – today
- 2023
[j28]Lorenzo Servadei, Jin Hwa Lee, José Antonio Arjona-Medina, Michael Werner, Sepp Hochreiter, Wolfgang Ecker, Robert Wille:
Deep Reinforcement Learning for Optimization at Early Design Stages. IEEE Des. Test 40(1): 43-51 (2023)- 2022
- [j27]Sepp Hochreiter:
Toward a broad AI. Commun. ACM 65(4): 56-57 (2022) - [j26]Philipp Seidl
, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer:
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. J. Chem. Inf. Model. 62(9): 2111-2120 (2022) - [j25]Theresa Roland, Carl Böck, Thomas Tschoellitsch, Alexander Maletzky, Sepp Hochreiter, Jens Meier, Günter Klambauer:
Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. J. Medical Syst. 46(5): 23 (2022) - [c34]Pedram Ghamisi, Omid Ghorbanzadeh, Yonghao Xu, Pedro Herruzo, David P. Kreil, Michael Kopp, Sepp Hochreiter:
The Landslide4Sense Competition 2022. CDCEO@IJCAI 2022: 91 - [c33]Fabian Paischer, Thomas Adler, Vihang P. Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-Zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. ICML 2022: 17156-17185 - [c32]Vihang P. Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, José Antonio Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. ICML 2022: 17531-17572 - [i41]Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. CoRR abs/2203.17070 (2022) - [i40]Fabian Paischer, Thomas Adler, Vihang P. Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. CoRR abs/2205.12258 (2022) - [i39]Bernhard Schäfl, Lukas Gruber, Angela Bitto-Nemling, Sepp Hochreiter:
Hopular: Modern Hopfield Networks for Tabular Data. CoRR abs/2206.00664 (2022) - [i38]Mathias Lechner, Ramin M. Hasani, Zahra Babaiee, Radu Grosu, Daniela Rus, Thomas A. Henzinger, Sepp Hochreiter:
Entangled Residual Mappings. CoRR abs/2206.01261 (2022) - [i37]Martin Gauch, Maximilian Beck, Thomas Adler, Dmytro Kotsur, Stefan Fiel, Hamid Eghbal-zadeh, Johannes Brandstetter, Johannes Kofler, Markus Holzleitner, Werner Zellinger, Daniel Klotz, Sepp Hochreiter, Sebastian Lehner:
Few-Shot Learning by Dimensionality Reduction in Gradient Space. CoRR abs/2206.03483 (2022) - [i36]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang P. Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning. CoRR abs/2207.05742 (2022) - [i35]Yonghao Xu, Weikang Yu, Pedram Ghamisi, Michael Kopp, Sepp Hochreiter:
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networks. CoRR abs/2208.04441 (2022) - 2021
- [j24]Andreu Vall, Yogesh Sabnis, Jiye Shi, Reiner Class, Sepp Hochreiter, Günter Klambauer:
The Promise of AI for DILI Prediction. Frontiers Artif. Intell. 4: 638410 (2021) - [j23]Markus Holzleitner, Lukas Gruber, José Antonio Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter:
Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. Trans. Large Scale Data Knowl. Centered Syst. 48: 105-130 (2021) - [c31]Pedro Herruzo, Aleksandra Gruca, Llorenç Lliso, Xavier Calbet, Pilar Rípodas, Sepp Hochreiter, Michael Kopp, David P. Kreil:
High-resolution multi-channel weather forecasting - First insights on transfer learning from the Weather4cast Competitions 2021. IEEE BigData 2021: 5750-5757 - [c30]Aleksandra Gruca, Pedro Herruzo, Pilar Rípodas, Andrzej Kucik, Christian Briese, Michael K. Kopp, Sepp Hochreiter, Pedram Ghamisi, David P. Kreil:
CDCEO'21 - First Workshop on Complex Data Challenges in Earth Observation. CIKM 2021: 4878-4879 - [c29]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David P. Kreil, Michael K. Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. ICLR 2021 - [c28]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. ICML 2021: 4275-4286 - [c27]Christian Eichenberger, Moritz Neun, Henry Martin, Pedro Herruzo, Markus Spanring, Yichao Lu, Sungbin Choi, Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman, Nina Wiedemann, Martin Raubal, Bo Wang, Hai L. Vu, Reza Mohajerpoor, Chen Cai, Inhi Kim, Luca Hermes, Andrew Melnik, Riza Velioglu, Markus Vieth, Malte Schilling, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Jay Santokhi, Dylan Hillier, Yiming Yang, Joned Sarwar, Anna Jordan, Emil Hewage, David Jonietz, Fei Tang, Aleksandra Gruca, Michael Kopp, David P. Kreil, Sepp Hochreiter:
Traffic4cast at NeurIPS 2021 - Temporal and Spatial Few-Shot Transfer Learning in Gridded Geo-Spatial Processes. NeurIPS (Competition and Demos) 2021: 97-112 - [i34]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. CoRR abs/2101.05186 (2021) - [i33]Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler:
Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications. CoRR abs/2103.16910 (2021) - [i32]Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. CoRR abs/2104.03279 (2021) - [i31]Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter:
Learning 3D Granular Flow Simulations. CoRR abs/2105.01636 (2021) - [i30]Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter:
Boundary Graph Neural Networks for 3D Simulations. CoRR abs/2106.11299 (2021) - [i29]Andreas Fürst, Elisabeth Rumetshofer, Viet Tran, Hubert Ramsauer, Fei Tang, Johannes Lehner, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto-Nemling, Sepp Hochreiter:
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. CoRR abs/2110.11316 (2021) - [i28]Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang P. Patil, Sepp Hochreiter:
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. CoRR abs/2111.04714 (2021) - 2020
- [j22]Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen:
Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics 12(1): 26 (2020) - [c26]Marius-Constantin Dinu, Markus Hofmarcher, Vihang P. Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
XAI and Strategy Extraction via Reward Redistribution. xxAI@ICML 2020: 177-205 - [c25]Lorenzo Servadei, Jiapeng Zheng, Jose A. Arjona-Medina, Michael Werner, Volkan Esen, Sepp Hochreiter, Wolfgang Ecker, Robert Wille:
Cost Optimization at Early Stages of Design Using Deep Reinforcement Learning. MLCAD 2020: 37-42 - [c24]Michael Kopp, David P. Kreil, Moritz Neun, David Jonietz, Henry Martin, Pedro Herruzo, Aleksandra Gruca, Ali Soleymani, Fanyou Wu, Yang Liu, Jingwei Xu, Jianjin Zhang, Jay Santokhi, Alabi Bojesomo, Hasan Al-Marzouqi, Panos Liatsis, Pak Hay Kwok, Qi Qi, Sepp Hochreiter:
Traffic4cast at NeurIPS 2020 ? yet more on theunreasonable effectiveness of gridded geo-spatial processes. NeurIPS (Competition and Demos) 2020: 325-343 - [c23]Michael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. NeurIPS 2020 - [i27]Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch, Philipp Renz, Johannes Schimunek, Philipp Seidl, Andreu Vall, Michael Widrich, Sepp Hochreiter, Günter Klambauer:
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks. CoRR abs/2004.00979 (2020) - [i26]Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlovic, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. CoRR abs/2007.13505 (2020) - [i25]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Milena Pavlovic, Geir Kjetil Sandve, Victor Greiff, David P. Kreil, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. CoRR abs/2008.02217 (2020) - [i24]Vihang P. Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. CoRR abs/2009.14108 (2020) - [i23]Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David P. Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter:
Cross-Domain Few-Shot Learning by Representation Fusion. CoRR abs/2010.06498 (2020) - [i22]Martin Gauch, Frederik Kratzert, Daniel Klotz, Grey Nearing, Jimmy Lin, Sepp Hochreiter:
Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network. CoRR abs/2010.07921 (2020) - [i21]Markus Holzleitner, Lukas Gruber, Jose A. Arjona-Medina, Johannes Brandstetter, Sepp Hochreiter:
Convergence Proof for Actor-Critic Methods Applied to PPO and RUDDER. CoRR abs/2012.01399 (2020) - [i20]Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. CoRR abs/2012.14295 (2020)
2010 – 2019
- 2019
- [j21]Günter Klambauer, Sepp Hochreiter, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 59(3): 945-946 (2019) - [j20]Markus Hofmarcher, Elisabeth Rumetshofer, Djork-Arné Clevert, Sepp Hochreiter, Günter Klambauer:
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks. J. Chem. Inf. Model. 59(3): 1163-1171 (2019) - [c22]Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl, Sepp Hochreiter, Günter Klambauer:
Human-level Protein Localization with Convolutional Neural Networks. ICLR (Poster) 2019 - [c21]David P. Kreil, Michael K. Kopp, David Jonietz, Moritz Neun, Aleksandra Gruca, Pedro Herruzo, Henry Martin, Ali Soleymani, Sepp Hochreiter:
The surprising efficiency of framing geo-spatial time series forecasting as a video prediction task - Insights from the IARAI Traffic4cast Competition at NeurIPS 2019. NeurIPS (Competition and Demos) 2019: 232-241 - [c20]Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter:
RUDDER: Return Decomposition for Delayed Rewards. NeurIPS 2019: 13544-13555 - [p6]Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek:
Explaining and Interpreting LSTMs. Explainable AI 2019: 211-238 - [p5]Markus Hofmarcher, Thomas Unterthiner, Jose A. Arjona-Medina, Günter Klambauer, Sepp Hochreiter, Bernhard Nessler:
Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. Explainable AI 2019: 285-296 - [p4]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. Explainable AI 2019: 331-345 - [p3]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. Explainable AI 2019: 347-362 - [i19]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. CoRR abs/1903.02788 (2019) - [i18]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. CoRR abs/1903.07903 (2019) - [i17]Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling. CoRR abs/1907.08456 (2019) - [i16]Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek:
Explaining and Interpreting LSTMs. CoRR abs/1909.12114 (2019) - [i15]Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter:
Patch Refinement - Localized 3D Object Detection. CoRR abs/1910.04093 (2019) - [i14]Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter:
Quantum Optical Experiments Modeled by Long Short-Term Memory. CoRR abs/1910.13804 (2019) - [i13]Frederik Kratzert, Daniel Klotz, Johannes Brandstetter, Pieter-Jan Hoedt, Grey Nearing, Sepp Hochreiter:
Using LSTMs for climate change assessment studies on droughts and floods. CoRR abs/1911.03941 (2019) - [i12]Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher, Philipp Tschandl, Harald Kittler, Sepp Hochreiter, Wolfram Hötzenecker, Günter Klambauer:
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. CoRR abs/1911.06616 (2019) - 2018
- [j19]Kristina Preuer, Richard P. I. Lewis, Sepp Hochreiter, Andreas Bender, Krishna C. Bulusu, Günter Klambauer:
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning. Bioinform. 34(9): 1538-1546 (2018) - [j18]Sepp Hochreiter, Günter Klambauer, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 58(9): 1723-1724 (2018) - [j17]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery. J. Chem. Inf. Model. 58(9): 1736-1741 (2018) - [c19]Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. ICLR (Poster) 2018 - [c18]Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter:
First Order Generative Adversarial Networks. ICML 2018: 4574-4583 - [i11]Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter:
First Order Generative Adversarial Networks. CoRR abs/1802.04591 (2018) - [i10]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemblNet Distance: A metric for generative models for molecules. CoRR abs/1803.09518 (2018) - [i9]Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Sepp Hochreiter:
RUDDER: Return Decomposition for Delayed Rewards. CoRR abs/1806.07857 (2018) - 2017
- [j16]Djork-Arné Clevert, Thomas Unterthiner, Gundula Povysil, Sepp Hochreiter:
Rectified factor networks for biclustering of omics data. Bioinform. 33(14): i59-i66 (2017) - [c17]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. NIPS 2017: 971-980 - [c16]Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter:
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. NIPS 2017: 6626-6637 - [i8]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. CoRR abs/1706.02515 (2017) - [i7]Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Sepp Hochreiter:
GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium. CoRR abs/1706.08500 (2017) - [i6]Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. CoRR abs/1708.08819 (2017) - 2016
- [c15]Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter:
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). ICLR (Poster) 2016 - 2015
- [j15]Johannes Palme, Sepp Hochreiter, Ulrich Bodenhofer:
KeBABS: an R package for kernel-based analysis of biological sequences. Bioinform. 31(15): 2574-2576 (2015) - [j14]Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map. Bioinform. 31(20): 3392-3394 (2015) - [j13]Ulrich Bodenhofer, Enrico Bonatesta, Christoph Horejs-Kainrath, Sepp Hochreiter:
msa: an R package for multiple sequence alignment. Bioinform. 31(24): 3997-3999 (2015) - [c14]Djork-Arné Clevert, Andreas Mayr, Thomas Unterthiner, Sepp Hochreiter:
Rectified Factor Networks. NIPS 2015: 1855-1863 - [i5]Djork-Arné Clevert, Thomas Unterthiner, Andreas Mayr, Hubert Ramsauer, Sepp Hochreiter:
Rectified Factor Networks. CoRR abs/1502.06464 (2015) - [i4]Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter:
Toxicity Prediction using Deep Learning. CoRR abs/1503.01445 (2015) - 2014
- [j12]Marc Streit, Samuel Gratzl, Michael Gillhofer, Andreas Mayr, Andreas Mitterecker, Sepp Hochreiter:
Furby: fuzzy force-directed bicluster visualization. BMC Bioinform. 15(S-6): S4 (2014) - 2013
- [i3]Andreas Bender, Hinrich W. H. Göhlmann, Sepp Hochreiter, Ziv Shkedy:
Computational Methods Aiding Early-Stage Drug Design (Dagstuhl Seminar 13212). Dagstuhl Reports 3(5): 78-94 (2013) - 2011
- [j11]Ulrich Bodenhofer, Andreas Kothmeier, Sepp Hochreiter:
APCluster: an R package for affinity propagation clustering. Bioinform. 27(17): 2463-2464 (2011) - 2010
- [j10]Sepp Hochreiter, Ulrich Bodenhofer, Martin Heusel, Andreas Mayr, Andreas Mitterecker, Adetayo Kasim, Tatsiana Khamiakova, Suzy Van Sanden, Dan Lin, Willem Talloen, Luc Bijnens, Hinrich W. H. Göhlmann, Ziv Shkedy, Djork-Arné Clevert:
FABIA: factor analysis for bicluster acquisition. Bioinform. 26(12): 1520-1527 (2010)
2000 – 2009
- 2009
- [c13]Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ionescu, Sepp Hochreiter:
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations. IFSA/EUSFLAT Conf. 2009: 1376-1381 - [e2]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
Similarity-based learning on structures, 15.02. - 20.02.2009. Dagstuhl Seminar Proceedings 09081, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany 2009 [contents] - [i2]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Abstracts Collection - Similarity-based learning on structures. Similarity-based learning on structures 2009 - [i1]Michael Biehl, Barbara Hammer, Sepp Hochreiter, Stefan C. Kremer, Thomas Villmann:
09081 Summary - Similarity-based learning on structures. Similarity-based learning on structures 2009 - 2008
- [j9]Tilman Knebel, Sepp Hochreiter, Klaus Obermayer:
An SMO Algorithm for the Potential Support Vector Machine. Neural Comput. 20(1): 271-287 (2008) - 2007
- [j8]Sepp Hochreiter, Martin Heusel, Klaus Obermayer:
Fast model-based protein homology detection without alignment. Bioinform. 23(14): 1728-1736 (2007) - [j7]Willem Talloen, Djork-Arné Clevert, Sepp Hochreiter, Dhammika Amaratunga, Luc Bijnens, Stefan Kass, Hinrich W. H. Göhlmann:
I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data. Bioinform. 23(21): 2897-2902 (2007) - [c12]Steffen Grünewälder, Sepp Hochreiter, Klaus Obermayer:
Optimality of LSTD and its Relation to MC. IJCNN 2007: 338-343 - [p2]Sepp Hochreiter, Michael C. Mozer:
Monaural Speech Separation by Support Vector Machines: Bridging the Divide Between Supervised and Unsupervised Learning Methods. Blind Speech Separation 2007: 411-428 - [e1]Sepp Hochreiter, Roland Wagner:
Bioinformatics Research and Development, First International Conference, BIRD 2007, Berlin, Germany, March 12-14, 2007, Proceedings. Lecture Notes in Computer Science 4414, Springer 2007, ISBN 978-3-540-71232-9 [contents] - 2006
- [j6]Sepp Hochreiter, Djork-Arné Clevert, Klaus Obermayer:
A new summarization method for affymetrix probe level data. Bioinform. 22(8): 943-949 (2006) - [j5]Sepp Hochreiter, Klaus Obermayer:
Support Vector Machines for Dyadic Data. Neural Comput. 18(6): 1472-1510 (2006) - [c11]Johannes Mohr, Imke Puls, Jana Wrase, Sepp Hochreiter, Andreas Heinz, Klaus Obermayer:
P-SVM Variable Selection for Discovering Dependencies Between Genetic and Brain Imaging Data. IJCNN 2006: 5020-5027 - [p1]Sepp Hochreiter, Klaus Obermayer:
Nonlinear Feature Selection with the Potential Support Vector Machine. Feature Extraction 2006: 419-438 - 2002
- [c10]Sepp Hochreiter, Michael Mozer, Klaus Obermayer:
Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. NIPS 2002: 545-552 - [c9]Sepp Hochreiter, Klaus Obermayer:
Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers. NIPS 2002: 889-896 - 2001
- [c8]Sepp Hochreiter, A. Steven Younger, Peter R. Conwell:
Learning to Learn Using Gradient Descent. ICANN 2001: 87-94 - [c7]Sepp Hochreiter, Michael Mozer:
A Discrete Probabilistic Memory Model for Discovering Dependencies in Time. ICANN 2001: 661-668 - 2000
- [c6]Sepp Hochreiter, Michael Mozer:
Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models. NIPS 2000: 535-541
1990 – 1999
- 1999
- [j4]Sepp Hochreiter, Jürgen Schmidhuber:
Feature Extraction Through LOCOCODE. Neural Comput. 11(3): 679-714 (1999) - [c5]Sepp Hochreiter, Jürgen Schmidhuber:
Nonlinear ICA through low-complexity autoencoders. ISCAS (5) 1999: 53-56 - 1998
- [j3]Sepp Hochreiter:
The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 6(2): 107-116 (1998) - [c4]Sepp Hochreiter, Jürgen Schmidhuber:
Source Separation as a By-Product of Regularization. NIPS 1998: 459-465 - 1997
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