Jan Adamowski
Environmental Engineering · 2000–2020
A researcher in the Science corpus: 20 papers; trusts 73 researchers and is trusted by 47 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 140 citations into it; #213 of 5,479 by trust here, #223 by citations
- Water Science and Technology — 92 citations into it; #88 of 1,711 by trust here, #279 by citations
- Artificial Intelligence — 90 citations into it
- Global and Planetary Change — 87 citations into it; #1,013 of 10,225 by trust here, #1,710 by citations
- Electrical and Electronic Engineering — 62 citations into it; #1,472 of 16,539 by trust here, #3,918 by citations
- Statistics and Probability — 22 citations into it
- Management Science and Operations Research — 20 citations into it
- Computer Vision and Pattern Recognition — 18 citations into it
Whom Jan Adamowski trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ozgur Kisi
- Stéphane Mallat
- Vladimir Naumovich Vapni
- Holger R. Maier
- Vladimir Naumovich Vapnik
- MohammadSajjad Khan
- G. Huang
- Ingrid Daubechies
- C. Wu
- Vahid Nourani
Who trusts Jan Adamowski overall
- Ravinesh C. Deo
- Mukesh Tiwari
- Zhiyong Liu
- Vahid Nourani
- Mohammad Ali Ghorbani
- Yuhu Zhang
- John M. Quilty
- Yurui Fan
- Farnaz Fotovatikhah
- V. Sehgal
Papers from Jan Adamowski's perspective
Ordered by how strongly the researchers Jan Adamowski trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Support-Vector Networks
- Long Short-Term Memory
- The Nature of Statistical Learning Theory
- Statistical Learning Theory
- Neural Networks for Pattern Recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. (2010) — 414 citations
- Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review (2014) — 675 citations
- Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models (2014) — 428 citations
- Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq (2016) — 299 citations
- Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model (2017) — 220 citations
- Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones (2020) — 75 citations
- Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model (2020) — 478 citations
- Soil fragmentation and aggregate stability as affected by conventional tillage implements and relations with fractal dimensions (2020) — 69 citations
- Evaluation of data-driven models (SVR and ANN) for groundwater-level prediction in confined and unconfined systems (2019) — 76 citations
- A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods (2019) — 629 citations
- Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting (2019) — 97 citations
- An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines. (2019) — 688 citations
- On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction (2019) — 98 citations
- Evaluation of data driven models for river suspended sediment concentration modeling (2016) — 121 citations
- Bootstrap rank‐ordered conditional mutual information (broCMI): A nonlinear input variable selection method for water resources modeling (2016) — 85 citations
- Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954–2008) (2012) — 261 citations
- Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada (2012) — 460 citations
- Development of a new method of wavelet aided trend detection and estimation (2009) — 149 citations
- Parity symmetry and energy spectrum of excitons in coupled self-assembled quantum dots (2001) — 132 citations
- Electron pair in a Gaussian confining potential (2000) — 189 citations