activity
20192021
most citedDifferentiable Particle Filtering without Modifying the Forward Pass

8 citations · 13 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2021

Proof of the impossibility of probabilistic induction

Vaden Masrani

In this short note I restate and simplify the proof of the impossibility of probabilistic induction from Popper (1992). Other proofs are possible (cf. Popper (1985)).

cs.LG20211 cited

q-Paths: Generalizing the Geometric Annealing Path using Power Means

Vaden Masrani, Rob Brekelmans, Thang Bui +4

Many common machine learning methods involve the geometric annealing path, a sequence of intermediate densities between two distributions of interest constructed using the geometri…

stat.ML20218 cited

Differentiable Particle Filtering without Modifying the Forward Pass

Adam Ścibior, Frank Wood

Particle filters are not compatible with automatic differentiation due to the presence of discrete resampling steps. While known estimators for the score function, based on Fisher'…

cs.LG20202 cited

Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective

Vu Nguyen, Vaden Masrani, Rob Brekelmans +2

Achieving the full promise of the Thermodynamic Variational Objective (TVO), a recently proposed variational lower bound on the log evidence involving a one-dimensional Riemann int…

cs.LG20202 cited

All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Rob Brekelmans, Vaden Masrani, Frank Wood +2

The recently proposed Thermodynamic Variational Objective (TVO) leverages thermodynamic integration to provide a family of variational inference objectives, which both tighten and…

cs.CV2019

Improved Few-Shot Visual Classification

Peyman Bateni, Raghav Goyal, Vaden Masrani +2

Few-shot learning is a fundamental task in computer vision that carries the promise of alleviating the need for exhaustively labeled data. Most few-shot learning approaches to date…