9 citations · 13 across the 7 of their papers we have counts for
8 papers
Theoretical Analysis of Thermodynamic Matrix Inversion: First-order Equivalence to Preconditioned Gradient Descent and Implications for Analog Computing
Gerhard Kirsten, Michael Selby, Janith Petangoda +3
Recent research has demonstrated the possibility of exploiting the thermodynamics of coupled electrical oscillators to implement computational tasks such as matrix inversion. While…
A Tensor Train Approach for Deterministic Arithmetic Operations on Discrete Representations of Probability Distributions
Gerhard Kirsten, Bilgesu Bilgin, Janith Petangoda +1
Computing with discrete representations of high-dimensional probability distributions is fundamental to uncertainty quantification, Bayesian inference, and stochastic modeling. How…
The Monte Carlo Method and New Device and Architectural Techniques for Accelerating It
Janith Petangoda, Chatura Samarakoon, James Meech +5
Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncert…
Sensitivity Analysis of the Laser Power Control System to Measurement Noise in SLS 3D Printers
Hamid Toshani, Janith Petangoda, Chatura Samarakoon +1
Uniform temperature distribution in Selective Laser Sintering (SLS) is essential for producing durable 3D prints. Achieving uniformity requires a laser power control system that mi…
Learning to Transfer: A Foliated Theory
Janith Petangoda, Marc Peter Deisenroth, Nicholas A. M. Monk
Learning to transfer considers learning solutions to tasks in a such way that relevant knowledge can be transferred from known task solutions to new, related tasks. This is importa…
GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability
Daniel Lengyel, Janith Petangoda, Isak Falk +5
We propose an efficient algorithm to visualise symmetries in neural networks. Typically, models are defined with respect to a parameter space, where non-equal parameters can produc…
A Foliated View of Transfer Learning
Janith Petangoda, Nick A. M. Monk, Marc Peter Deisenroth
Transfer learning considers a learning process where a new task is solved by transferring relevant knowledge from known solutions to related tasks. While this has been studied expe…
Disentangled Skill Embeddings for Reinforcement Learning
Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam +2
We propose a novel framework for multi-task reinforcement learning (MTRL). Using a variational inference formulation, we learn policies that generalize across both changing dynamic…