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Misfolded tau proteins play a critical role in the progression and pathology of Alzheimer's disease.
The wave of advance of advantageous genes
Ronald Aylmer Fisher · 1937
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A study of the equation of diffusion with increase in the quantity of matter, and its application to a biological problem
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Finite bandwidth, finite amplitude convection
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Distant side-walls cause slow amplitude modulation of cellular convection
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Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization
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Multi-element generalized polynomial chaos for arbitrary probability measures
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Parameterizable consensus connectomes from the human connectome project: the budapest reference connectome server v3. 0
Balázs Szalkai, Csaba Kerepesi, Bálint Varga, and Vince Grolmusz · 2017
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Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Maziar Raissi, Paris Perdikaris, and George E Karniadakis · 2019
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fPINNs: Fractional physics-informed neural networks
Guofei Pang, Lu Lu, and George Em Karniadakis · 2019
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Spread of α \alpha -synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis
M X Henderson, E J Cornblath, A Darwich, B Zhang, H Brown, R J Gathagan, R M Sandler, D S Bassett, T J Trojanowski, and Lee V M Y · 2019
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Connectomics of neurodegeneration
Ellen Kuhl · 2019
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Prion-like spreading of alzheimer’s disease within the brain’s connectome
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Discovering symbolic models from deep learning with inductive biases
Miles Cranmer, Alvaro Sanchez Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, and Shirley Ho · 2020
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Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems
Ameya D Jagtap, Ehsan Kharazmi, and George Em Karniadakis · 2020
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Bayesian Physics Informed Neural Networks for real-world nonlinear dynamical systems
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Zongren Zou, Xuhui Meng, Apostolos F Psaros, and George Em Karniadakis · 2022
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A PINN approach to symbolic differential operator discovery with sparse data
Lena Podina, Brydon Eastman, and Mohammad Kohandel · 2022
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S Berrone, C Canuto, M Pintore, and N Sukumar · 2022
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Interpretable machine learning for science with PySR and SymbolicRegression. jl
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