Workshop
Sat Dec 12 04:50 AM -- 03:00 PM (PST)
Machine Learning for Engineering Modeling, Simulation and Design
For full details see: [ protected link dropped ]
Modern engineering workflows are built on computational tools for specifying models and designs, for numerical analysis of system behavior, and for optimization, model-fitting and rational design. How can machine learning be used to empower the engineer and accelerate this workflow? We wish to bring together machine learning researchers and engineering academics to address the problem of developing ML tools which benefit engineering modeling, simulation and design, through reduction of required computational or human effort, through permitting new rich design spaces, through enabling production of superior designs, or through enabling new modes of interaction and new workflows.
| Opening Remarks (Live) | |
| Nils Thuerey - Lead the Way! Deep Learning via Differentiable Simulations (Invited talk) | |
| Nils Thuerey Q&A (Q&A) | |
| Angela Dai - Self-supervised generation of 3D shapes and scenes (Invited talk) | |
| Angela Dai Q&A (Q&A) | |
| Poster Session 1 (gather.town poster session) | |
| Tatiana Lopez-Guevara - Robots, Liquids & Inference (Invited talk) | |
| Tatiana Lopez-Guevara Q&A (Q&A) | |
| Peter Battaglia - Structured models of physics, objects, and scenes (Invited talk) | |
| Peter Battaglia Q&A (Q&A) | |
| Break | |
| Panel discussion with invited speakers (Panel discussion) | |
| Karen E Willcox - Operator Inference: Bridging model reduction and scientific machine learning (Invited talk) | |
| Karen E Willcox Q&A (Q&A) | |
| Grace X Gu - Artificial intelligence for materials design and additive manufacturing (Invited talk) | |
| Grace X Gu Q&A (Q&A) | |
| Closing remarks (Live) | |
| Poster Session 2 (gather.town poster session) | |
| On the Effectiveness of Bayesian AutoML methods for Physics Emulators (Poster) | |
| Collaborative Multidisciplinary Design Optimization with Neural Networks (Poster) | |
| Accelerating Inverse Design of Nanostructures Using Manifold Learning (Poster) | |
| Efficient Nanopore Optimization by CNN-accelerated Deep Reinforcement Learning (Poster) | |
| Building LEGO using Deep Generative Models of Graphs (Poster) | |
| Electric Vehicle Range Improvement by Utilizing Deep Learning to Optimize Occupant Thermal Comfort (Poster) | |
| A Learning-boosted Quasi-Newton Method for AC Optimal Power Flow (Poster) | |
| Differentiable Implicit Layers (Poster) | |
| On Training Effective Reinforcement Learning Agents for Real-time Power Grid Operation and Control (Poster) | |
| Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes (Poster) | |
| A General Framework Combining Generative Adversarial Networks and Mixture Density Networks for Inverse Modeling in Microstructural Materials Design (Poster) | |
| Simultaneous Process Design and Control Optimization using Reinforcement Learning (Poster) | |
| Scalable Combinatorial Bayesian Optimization with Tractable Statistical models (Poster) | |
| A Sequential Modelling Approach for Indoor Temperature Prediction and Heating Control in Smart Buildings (Poster) | |
| Probabilistic Adjoint Sensitivity Analysis for Fast Calibration of Partial Differential Equation Models (Poster) | |
| Combinatorial 3D Shape Generation via Sequential Assembly (Poster) | |
| Multi-Loss Sub-Ensembles for Accurate Classification with Uncertainty Estimation (Poster) | |
| Prediction of high frequency resistance in polymer electrolyte membrane fuel cells using Long Short Term Memory based model (Poster) | |
| Continuous calibration of a digital twin; a particle filter approach (Poster) | |
| An Industrial Application of Deep Reinforcement Learning for Chemical Production Scheduling (Poster) | |
| Surrogates for Stiff Nonlinear Systems using Continuous Time Echo State Networks (Poster) | |
| Multilevel Delayed Acceptance MCMC with an Adaptive Error Model in PyMC3 (Poster) | |
| Parameterized Reinforcement Learning for Optical System Optimization (Poster) | |
| Signal Enhancement for Magnetic Navigation Challenge Problem (Poster) | |
| Battery Model Calibration with Deep Reinforcement Learning (Poster) | |
| Uncertainty-aware Remaining Useful Life predictors (Poster) | |
| Rethink AI-based Power Grid Control: Diving Into Algorithm Design (Poster) | |
| Data-driven inverse design optimization of magnetically programmed soft structures (Poster) | |
| End-to-End Differentiability and Tensor Processing Unit Computing to Accelerate Materials’ Inverse Design (Poster) | |
| Learning to Identify Drilling Defects in TurbineBlades with Single Stage Detectors (Poster) | |
| Efficient nonlinear manifold reduced order model (Poster) | |
| Frequency-compensated PINNs for Fluid-dynamic Design Problems (Poster) | |
| Context-Aware Urban Energy Efficiency Optimization Using Hybrid Physical Models (Poster) | |
| Model Order Reduction using a Deep Orthogonal Decomposition (Poster) | |
| Information-Theoretic Multi-Objective Bayesian Optimization with Continuous Approximations (Poster) | |
| Learning Mesh-Based Simulation with Graph Networks (Poster) | |
| Robotic gripper design with Evolutionary Strategies and Graph Element Networks (Poster) | |
| Scalable Deep-Learning-Accelerated Topology Optimization for Additively Manufactured Materials (Poster) | |
| Modular mobile robot design selection with deep reinforcement learning (Poster) | |
| Flaw Detection in Metal Additive Manufacturing Using Deep Learned Acoustic Features (Poster) | |
| Exact Preimages of Neural Network Aircraft Collision Avoidance Systems (Poster) | |
| Predicting Nanorobot Shapes via Generative Models (Poster) | |
| A Nonlocal-Gradient Descent Method for Inverse Design in Nanophotonics (Poster) | |
| Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing (Poster) | |
| Jacobian of Conditional Generative Models for Sensitivity Analysis of Photovoltaic Device Processes (Poster) | |
| TPINN: An improved architecture for distributed physics informed neural networks (Poster) | |
| Heat risk assessment using surrogate model for meso-scale surface temperature (Poster) | |
| Analog Circuit Design with Dyna-Style Reinforcement Learning (Poster) | |
| A data centric approach to generative modelling of rough surfaces: An application to 3D-printed Stainless Steel (Poster) | |
| Bayesian polynomial chaos (Poster) | |
| Constraint active search for experimental design (Poster) | |
| Machine Learning-based Anomaly Detection with Magnetic Data (Poster) | |
| ManufacturingNet: A machine learning tool for engineers (Poster) | |
| An adversarially robust approach to security-constrained optimal power flow (Poster) | |
| Real-time Prediction of Soft Tissue Deformations Using Data-driven Nonlinear Presurgical Simulations (Poster) | |
| Decoding the genome of cement by Gaussian Process Regression (Poster) | |
| Multi-stage Transmission Line Flow Control Using Centralized and Decentralized Reinforcement Learning Agents (Poster) | |
| Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning (Poster) | |
| Scalable Multitask Latent Force Models with Applications to Predicting Lithium-ion Concentration (Poster) | |
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