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Found 7 papers, 2 papers with code
Extended Kalman Filtering for Recursive Online Discrete-Time Inverse Optimal Control
We formulate the discrete-time inverse optimal control problem of inferring unknown parameters in the objective function of an optimal control problem from measurements of optimal states and controls as a nonlinear filtering problem.
Transfer Learning for Microstructure Segmentation with CS-UNet: A Hybrid Algorithm with Transformer and CNN Encoders
Our result partially confirms the NASA study that the segmentation performance of out-of-distribution images (taken under different imaging and sample conditions) is significantly improved when pre-training on microscopy images.
Computer Vision Methods for the Microstructural Analysis of Materials: The State-of-the-art and Future Perspectives
Finding quantitative descriptors representing the microstructural features of a given material is an ongoing research area in the paradigm of Materials-by-Design.
Efficient Memory Partitioning in Software Defined Hardware
As programmers turn to software-defined hardware (SDH) to maintain a high level of productivity while programming hardware to run complex algorithms, heavy-lifting must be done by the compiler to automatically partition on-chip arrays.
Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator
Recurrent Neural Network (RNN) applications form a major class of AI-powered, low-latency data center workloads.
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark
In this work, we analyze the entries from DAWNBench, which received optimized submissions from multiple industrial groups, to investigate the behavior of TTA as a metric as well as trends in the best-performing entries.
DeepDSL: A Compilation-based Domain-Specific Language for Deep Learning
In this paper, we present DeepDSL, a domain specific language (DSL) embedded in Scala, that compiles deep networks written in DeepDSL to Java source code.
