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Found 4 papers, 0 papers with code
Ode to an ODE
We present a new paradigm for Neural ODE algorithms, called ODEtoODE, where time-dependent parameters of the main flow evolve according to a matrix flow on the orthogonal group O(d).
Geometrically Coupled Monte Carlo Sampling
Monte Carlo sampling in high-dimensional, low-sample settings is important in many machine learning tasks.
On Blackbox Backpropagation and Jacobian Sensing
From a small number of calls to a given “blackbox" on random input perturbations, we show how to efficiently recover its unknown Jacobian, or estimate the left action of its Jacobian on a given vector.
Adaptive Anonymity via b-Matching
The adaptive anonymity problem is formalized where each individual shares their data along with an integer value to indicate their personal level of desired privacy.
