Search Results
Catala: A Programming Language for the Law
Law at large underpins modern society, codifying and governing many aspects of citizens' daily lives.
Programming Languages
Identifying concept libraries from language about object structure
Our understanding of the visual world goes beyond naming objects, encompassing our ability to parse objects into meaningful parts, attributes, and relations.
Multi$^{\mathbf{3}}$Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
We propose a novel approach for rapid segmentation of flooded buildings by fusing multiresolution, multisensor, and multitemporal satellite imagery in a convolutional neural network.
A differentiable programming method for quantum control
Optimal control is highly desirable in many current quantum systems, especially to realize tasks in quantum information processing.
Quantum Physics Disordered Systems and Neural Networks Computational Physics
Dynamic virtual ecosystems as a tool for detecting large-scale responses of biodiversity to environmental and land-use change
These simulated ecosystems support the ability to generate many different types of habitat, as well as reproducing different disturbance scenarios such as climate change, habitat loss and invasion.
Control of Stochastic Quantum Dynamics by Differentiable Programming
We apply this approach to the state preparation and stabilization of a qubit subjected to homodyne detection.
Automated Fuzzing of Automotive Control Units
The harness detects physical responses, which we then use in a oracle functions to inform the fuzzing process.
Cryptography and Security Systems and Control Systems and Control
Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
There are two levels of symbol grounding problems among the core challenges: the first is symbol assignment, i. e. mapping latent factors of neural visual generators to semantic-meaningful symbolic factors from the reasoning systems by learning from limited labeled data.
A general characterization of optimal tie-breaker designs
When the running variable distribution is not symmetric or the fraction of subjects receiving the treatment is not $1/2$, our optimal designs improve upon a $D$-optimality objective without sacrificing short-term gain, compared to the three level tie-breaker designs of Owen and Varian (2020) that fix treatment probabilities at $0$, $1/2$, and $1$.
Methodology Econometrics Statistics Theory Statistics Theory
