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Found 10 papers, 5 papers with code
Parallel Proportional Fusion of Spiking Quantum Neural Network for Optimizing Image Classification
The recent emergence of the hybrid quantum-classical neural network (HQCNN) architecture has garnered considerable attention due to the potential advantages associated with integrating quantum principles to enhance various facets of machine learning algorithms and computations.
Computational Discovery of Microstructured Composites with Optimal Stiffness-Toughness Trade-Offs
The conflict between stiffness and toughness is a fundamental problem in engineering materials design.
Complex Locomotion Skill Learning via Differentiable Physics
Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers.
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Experimental results suggest that 1) RL-based approaches struggle to solve most of the tasks efficiently; 2) gradient-based approaches, by optimizing open-loop control sequences with the built-in differentiable physics engine, can rapidly find a solution within tens of iterations, but still fall short on multi-stage tasks that require long-term planning.
AsyncTaichi: On-the-fly Inter-kernel Optimizations for Imperative and Spatially Sparse Programming
These domain-specific optimizations further make way for classical general-purpose optimizations that are originally challenging to directly apply to computations with sparse data structures.
Learning-In-The-Loop Optimization: End-To-End Control And Co-Design Of Soft Robots Through Learned Deep Latent Representations
We validate the behavior of our algorithm with visualizations of the learned representation.
DiffTaichi: Differentiable Programming for Physical Simulation
We present DiffTaichi, a new differentiable programming language tailored for building high-performance differentiable physical simulators.
ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Robotics
The underlying physical laws of deformable objects are more complex, and the resulting systems have orders of magnitude more degrees of freedom and therefore they are significantly more computationally expensive to simulate.
Exposure: A White-Box Photo Post-Processing Framework
Retouching can significantly elevate the visual appeal of photos, but many casual photographers lack the expertise to do this well.
FC4: Fully Convolutional Color Constancy With Confidence-Weighted Pooling
However, the patch-based CNNs that exist for this problem are faced with the issue of estimation ambiguity, where a patch may contain insufficient information to establish a unique or even a limited possible range of illumination colors.
