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Found 7 papers, 1 papers with code
Quantum Natural Language Processing
In this context, we argue that "hallucinations" in modern artificial intelligence systems are a misunderstanding of the way facts are conceptualized: language can express many plausible hypotheses, of which only a few become actual.
KrADagrad: Kronecker Approximation-Domination Gradient Preconditioned Stochastic Optimization
Second order stochastic optimizers allow parameter update step size and direction to adapt to loss curvature, but have traditionally required too much memory and compute for deep learning.
SKI to go Faster: Accelerating Toeplitz Neural Networks via Asymmetric Kernels
For the low rank component, we replace the RPE MLP with linear interpolation and use asymmetric Structured Kernel Interpolation (SKI) (Wilson et.
Single Index Latent Variable Models for Network Topology Inference
A semi-parametric, non-linear regression model in the presence of latent variables is applied towards learning network graph structure.
EigenNetworks
Algorithms for learning the time series of graphs $\left\{G_k\right\}$, deriving the eigennetworks, eigenfeatures and eigentrajectories, and detecting changepoints are presented.
SILVar: Single Index Latent Variable Models
A semi-parametric, non-linear regression model in the presence of latent variables is introduced.
Signal Processing on Graphs: Causal Modeling of Unstructured Data
Many applications collect a large number of time series, for example, the financial data of companies quoted in a stock exchange, the health care data of all patients that visit the emergency room of a hospital, or the temperature sequences continuously measured by weather stations across the US.
