Machine Learning + X Seminars 2019 – The Crunch Group

December 27, 2019: A machine learning framework for solving high-dimensional mean field game and mean field control problemsing by Liu Yang
December 27, 2019: Learning to Reconstruct Crack Profiles for Eddy Current Nondestructive Testing by Enrui Zhang
December 19, 2019: Introducting AdaNet- Fast and Flexible AutoML with Learning Guarantees (Tutorial) and AdaNet- Adaptive Structural Learning of Artifical Neural Networkby Guofei Pang and Liu Yang
December 13, 2019: Turbulance Control – Better, Faster and Easier with Machine Learning by Bernd R. Noack from LIMSI, CNRS, University Paris-Saclay, France; TU Berlin; TU Braunschweig & HITSZ
December 13, 2019: Simulation of droplet using many-body dissipative particle dynamics and machine learning potentials for atomistic simulations by Chensen Lin
December 6, 2019: A Few Ideas from Neurobiology for Unsupervised Learning by Dmitry Krotov & Leopold Grinberg from IBM Research
November 22, 2019: The problem of inverse wave scattering: classical techniques and emerging approaches by L.D. Negro
November 15, 2019: Scientific Machine Learning with domain awarness: Theory Algotithms & Software by Lu Lu
November 15, 2019: Structure preserving schemes for complex nonlinear systems by Jie Shen
November 8, 2020: Calibrating nonlocal diffusion and turbulence models using PINNs by G. Pang
November 1, 2019: 3D Multi Source Localisation of Underwater Objects using Artificial Lateral Lines and Convolutional Neural Networks by Cai, Shengze colllaborating with M. L. Yin
November 1, 2019: Dimension redtion for increasing power in genomics by G. Darnell
October 25, 2019: An entropy viscosity method for simulation of flows at high Reynolds number with applications from aerodynamics to chronic man’s problem by Z. Wang
October 25, 2019: Application of PINNs on flow estimation problems based on limited measurements by Z. lIU
October 18, 2019: DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators by Lu Lu
October 18, 2019: DIRECT SHAPE OPTIMIZATION THROUGH DEEP REINFORCEMENT LEARNING by Ameya Jagtap
October 18, 2019: Replacing sea ics-wave interactions with superparameterization and machine learning by Christopher Horvat
October 4, 2019: Benchmarking TPU, GPU, and CPU Platforms for Deep Learning by Khemraj Shukla
October 4, 2019: Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning by Yang Liu
Adjoint-based olfactory search algorithm in turbulent environments by Yosuke Hasegawa.
September 27, 2019: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet by Xuhui Meng
September 27, 2019: Which Deep Learning Framework is Growing Fastest? TensorFlow vs. PyTorch, Minglang Yin
September 13, 2019: An efficient spectral approximation to singular problems with one-point singularity by Sheng Chen
September 13, 2019: An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications by Enrui Zhang
September 6, 2019: An empirical model of large batch training by Xiaowei Jin
September 6, 2019: Accurate, large minibatch sgd: Training imagenet in 1 hour by Xiaowei Jin
September 6, 2019: A new generation of PINN: Systems Biology Informed Deep Learning: Inferring Hidden Dynamics and Parameters by Alireza Yazdani
August 30, 2019: Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry by Qian Zhang
August 30, 2019: Physically informed artificial neural networks for atomistic modeling of materials by Qian Zhang
August 30, 2019: Machine learning of coarse-grained molecular dynamics force fields by Yixiang Deng
August 30, 2019: Boltzmann generators-sampling equilibrium states of many-body systems with deep learning by Yixiang Deng
August 23, 2019: Potential Flow Generator with $L_2$ Optimal Transport Regularity for Generative Models by Gan Liu
August 23, 2019: Deep-PIV: particle image velocimetry via deep learning techniques by Shengze Cai
August 16, 2019: Improving Simple Models with Confidence Profiles by Lu Lu
August 16, 2019: Quantifying PINN performance on Chaotic ODEs (Mathieu’s Equation) by George Karniadakis
August 8, 2019: Data-driven modeling of stochastic systems with adversarial deep learning by Paris Perdikaris
August 2, 2019: Highlights of Deep Learning for Science School by Guofei Pang and Lu Lu
July 26, 2019: When multiscale computation, Parareal and PINN have a party by Zhen Li
July 26, 2019: Single-Particle Diffusion Characterization by Deep Learning by He Li
July 19, 2019: Image analysis and machine learning for detecting malaria by Shaoqing Yu
July 19, 2019: Can semantic inpainting inspire hydrogeologist? by Qiang Zhang
July 12, 2019: Vascular Network Structure and Its Transport Properties in Mouse Retina by Yosuke Hasegawa
July 12, 2019: Recurrent Neural Networks and reservoir computing for spatio-temporal forcasting of chaotic dynamics by Yan Liu
June 21, 2019: Paper reviews: 1) Diagnosing Pregnancy Based on Wrist Pulse Wave, 2) Human Pulse Recognition based on Convolutional Neural Networks and 3) Wrist Pulse Signals Analysis based on Deep Convolutional Neural Network by Xiaoli Chen
June 21, 2019: Deep learning observables in computational fluid dynamics by Ameya D. Jagtap
June 14, 2019: Deep Learning for Ocean Remote Sensing: An Application of Convolutional Neural Networks for Super-Resolution on Satellite-Derived SST Data by Xiang Li
June 14, 2019: Applications of Deep Learning to Ocean Data Inference and Subgrid Parameterization by Xiang Li
June 14, 2019: The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies by Guofei Pang
June 7, 2019: Can PINNs beat FWI by Yiran Xu
June 7, 2019: Graph Embedding method for Network data analysis by Mengjia Xu.
May 31, 2019: Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness. by Pengzhan Jin
May 31, 2019: MoGlow: Probabilistic and controllable motion synthesis using normalising flows by Liu Yang
May 24, 2019: Super-resolution reconstruction of turbulent flows with machine learning by Xiaowei Jin
May 24, 2019: Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam by Ehsan Kharazmi
May 10, 2019: Bridging Finite Element and Machine Learning Modeling: Stress Prediction of Arterial Walls in Atherosclerosis by Xiaoning Zheng
May 10, 2019: Deep relaxation: partial differential equations for optimizing deep neural networks by Yeonjong Shin
May 3, 2019: Data driven nonlinear dynamical systems identification using multi-step CLDNN by Zhiping Mao
Recent applications of neural networks in biological systems
May 3, 2019: A synthetic turbulent inflow generator using machine learning by Fangying Song
May 3, 2019: End-to-end differentiable learning of protein structure by Yixiang Deng
May 3, 2019: Learning-based screening of hematologic disorders using quantitative phase imaging of individual red blood cells by Yixiang Deng
April 26, 2019: Spectral Normalization for Generative Adversarial Networks by Liu Yang
April 26, 2019: Generative Modeling using the Sliced Wasserstein Distance by Liu Yang
April 26, 2019: Sliced Wasserstein Generative Models by Liu Yang
April 26, 2019: Understanding training and generalization in deep learning by Fourier analysis by Xuhui Meng
April 22, 2019: An analysis of training and generalization errors in shallow and deep networks by Hrushikesh Mhaskar
April 22, 2019: Deep vs. Shallow Networks: an Approximation Theory Perspective by Hrushikesh Mhaskar
April 19, 2019: Predicting the solutions of heterogeneous elliptic PDEs with a confidence interval by probabilistic convolutional neural networks by Guofei Pang
April 19, 2019: Error bounds for approximations with deep ReLU neural networks in W^{s,p} norms by Mamikon Gulian
April 19, 2019: Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations by Mamikon Gulian
April 12, 2019: Assessment of End-to-End and Sequential Data-driven Learning of Fluid Flows by Ameya Jagtap
April 12, 2019: An introduction to the application of GANs in hydrogeology by Qiang Zheng
April 12, 2019: Physics-Informed Neurak Networkd (PINNs) for high speed flows by Zhiping Mao
April 5, 2019: Learning Noise-Invariant Representations for Robust Speech Recognition by Zhiping Mao and Xuhui Meng
April 5, 2019: Stochastic modeling of data-driven complex systems using machine learning tools by Dongkun Zhang
March 29, 2019: Boost your research through SciCoNet and Sums Job by Lu Lu
March 22, 2019: Deep Fluids: A Generative Network for Parameterized Fluid Simulations by Minglang Yin
March 22, 2019: Deep Potential: a general representation of a many-body potential energy surface by Zhen Li
March 15, 2019: Optimal approximation of continuous functions by very deep ReLU networks by Mamikon Gulian
March 15, 2019: Coarse Independent Particles using Mori-Zwanzig Theory by Mark Thachuk
March 1, 2019: Numerical solution of some evolutionary partial differential equations by Ameya Jagtap
March 1, 2019: Artificial Neural Networks Trained Through Deep Reimforcement Learning Discover Control Strategies for Active Flow Control by Ameya Jagtap
February 22, 2019: An inverse problem framework for extracting phonon properties from thermal spectroscopy measurments by Mojtaba Forghani, MIT
February 22, 2019: Elimination of All Bad Local Minima in Deep Learning by Yeonjong Shin
A review of definitions of fractional derivatives and other operators by Ehsan Kharazmi

February 15, 2019: Recurrent neural networks for visual processing by Drew Linsley, Junkying Kim & Thomas Serre
February 8, 2019: The Acquisition and Uncertainty Quantification of Land Surface Evapotranspiration at the Satellite Pixel Scale by Xiang Li
February 8, 2019: Vascular Network of Zebrafish Brain by Yosuke Hasegawa
February 8, 2019: Parametric study of single-particle dissipative particle dynamics model and its application by Yi Wang
February 1, 2019: Multifidelity and Machine Learning for Turbulent Flows by Ludger Paehler, Technische Universität München
February 1, 2019: Data-Driven Multiscale Modeling in Physical and Biological Systems by Alireza Yazdani
Prediction of atomization energy using graph kernel and active learning by Dr. Yu-Hang Tang, Lawrence Berkeley National Laboratory
January 25 2019: Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks by Guofei Pang
January 25, 2019: Introduction to ResNet by Lu Lu
January 11, 2019: pH-responsive polymer-grafted nanoparticles: From colloidal monolayer to Pickering emulsion by Shiyi Qin, State University of NY at Binghamton
January 11, 2019: Dynamic response and hydrodynamics of polarized crowds by Zhen Li