Sepp Hochreiter
Researcher Next ID · RN-021065
Researcher · Computer Science
Johannes Kepler University of Linz
Linz, Austria
- Works count
- 318
- Citation count
- 128,061
- H-index
- 54
- i10-index
- 115
Research interests
Publications
Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning
Water Resources Research · 2019 · 10.1029/2019wr026065
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL
Chemical Science · 2018 · 10.1039/c8sc00148k
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
arXiv (Cornell University) · 2017 · https://doi.org/10.48550/arxiv.1706.08500
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash\n Equilibrium
arXiv (Cornell University) · 2017 · https://doi.org/10.48550/arxiv.1706.08500
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
Bioinformatics · 2017 · 10.1093/bioinformatics/btx806
DeepTox: Toxicity Prediction using Deep Learning
Frontiers in Environmental Science · 2016 · 10.3389/fenvs.2015.00080
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
arXiv (Cornell University) · 2015 · https://doi.org/10.48550/arxiv.1511.07289
msa: an R package for multiple sequence alignment
Bioinformatics · 2015 · 10.1093/bioinformatics/btv494
The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 1998 · https://doi.org/10.1142/s0218488598000094
Flat Minima
Neural Computation · 1997 · 10.1162/neco.1997.9.1.1
Long Short-Term Memory
Neural Computation · 1997 · https://doi.org/10.1162/neco.1997.9.8.1735
LSTM can Solve Hard Long Time Lag Problems
Journal · 1996
Current projects
No projects listed.