Danielle Maddix
Danielle Maddix
Verified email at stanford.edu
Title
Cited by
Cited by
Year
Deep factors for forecasting
Y Wang, A Smola, D Maddix, J Gasthaus, D Foster, T Januschowski
International Conference on Machine Learning, 6607-6617, 2019
342019
Gluonts: Probabilistic time series models in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
arXiv preprint arXiv:1906.05264, 2019
262019
Neural forecasting: Introduction and literature overview
K Benidis, SS Rangapuram, V Flunkert, B Wang, D Maddix, C Turkmen, ...
arXiv preprint arXiv:2004.10240, 2020
192020
Deep factors with gaussian processes for forecasting
DC Maddix, Y Wang, A Smola
arXiv preprint arXiv:1812.00098, 2018
112018
GluonTS: Probabilistic and Neural Time Series Modeling in Python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
Journal of Machine Learning Research 21 (116), 1-6, 2020
102020
GluonTS: Probabilistic Time Series Modeling in Python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
arXiv preprint arXiv:1906.05264, 2019
62019
Numerical artifacts in the discontinuous Generalized Porous Medium Equation: How to avoid spurious temporal oscillations
DC Maddix, L Sampaio, M Gerritsen
Journal of Computational Physics 368, 277-298, 2018
42018
Numerical Artifacts in the Generalized Porous Medium Equation: Why Harmonic Averaging Itself Is Not to Blame
D Maddix, M Gerritsen, L Sampaio
Journal of Computational Physics 361, 280-298, 2018
42018
Advanced fluid reduced order models for compressible flow
I Tezaur, J Fike, K Carlberg, M Barone, D Maddix, E Mussoni, ...
Tech. Rep., 2017
22017
Diagnosing malignant versus benign breast tumors via machine learning techniques in high dimensions
DC Maddix
Stanford Univ., Stanford, CA, USA, Tech. Rep, 2014
22014
Minres: Sparse symmetric equations
CC Paige, MA Saunders, SC Choi, D Orban, UE Villa, D Maddix, S Regev
22004
Bridging Physics-based and Data-driven modeling for Learning Dynamical Systems
R Wang, D Maddix, C Faloutsos, Y Wang, R Yu
arXiv preprint arXiv:2011.10616, 2020
12020
Attention-based Domain Adaptation for Time Series Forecasting
X Jin, Y Park, D Maddix, Y Wang, X Yan
arXiv preprint arXiv:2102.06828, 2021
2021
Learning Dynamical Systems Requires Rethinking Generalization
R Wang, D Maddix, C Faloutsos, W Yuyang, R Yu
Interpretable Inductive Bias and Physically Structured Learning NeurIPS Workshop, 2020
2020
AutoODE: Bridging Physics-based and Data-driven modeling for COVID-19 Forecasting
R Wang, D Maddix, C Faloutsos, Y Wang, R Yu
2020
Neural time series models with GluonTS Time Series Workshop ICML 2019
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
2019
Numerical Artifacts in the Generalized Porous Medium Equation and Solutions
DC Maddix
Stanford University, 2018
2018
Structure and Parameter Learning in Bayesian Networks with Applications to Predicting Breast Cancer Tumor Malignancy in a Lower Dimension Feature Space
D Maddix
2016
Investigating the Effects of MINRES with Local Reorthogonalization
DC Maddix
2015
Using Numerical Optimization Methods to find Hamiltonian Cycle in Directed Graph
DC Maddix
2014
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Articles 1–20