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Found 6 papers, 2 papers with code
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs
Parameter identification and comparison of dynamical systems is a challenging task in many fields.
On the Existence of Universal Lottery Tickets
The lottery ticket hypothesis conjectures the existence of sparse subnetworks of large randomly initialized deep neural networks that can be successfully trained in isolation.
Discrete Sampling using Semigradient-based Product Mixtures
We consider the problem of inference in discrete probabilistic models, that is, distributions over subsets of a finite ground set.
Sampling from Probabilistic Submodular Models
Submodular and supermodular functions have found wide applicability in machine learning, capturing notions such as diversity and regularity, respectively.
Strong Log-Concavity Does Not Imply Log-Submodularity
We disprove a recent conjecture regarding discrete distributions and their generating polynomials stating that strong log-concavity implies log-submodularity.
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Modeling the time evolution of discrete sets of items (e. g., genetic mutations) is a fundamental problem in many biomedical applications.
