Aditya Ravuri

According to our database, Aditya Ravuri authored at least 15 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Transformers as Unrolled Inference in Probabilistic Laplacian Eigenmaps: An Interpretation and Potential Improvements.

Aditya Ravuri, Neil D. Lawrence

CoRR, July, 2025

Protein Language Model Zero-Shot Fitness Predictions are Improved by Inference-only Dropout.

Aditya Ravuri, Neil D. Lawrence

CoRR, June, 2025

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs.

Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy

J. Mach. Learn. Res., 2025

Towards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models.

Konstantin Donhauser, Kristina Ulicna, Gemma E. Moran, Aditya Ravuri, Kian Kenyon-Dean, Cian Eastwood, Jason S. Hartford

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

On Feature Learning for Titi Monkey Activity Detection.

Aditya Ravuri, Jen Muir, Neil D. Lawrence

CoRR, 2024

Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE.

Aditya Ravuri, Neil D. Lawrence

CoRR, 2024

Scalable Amortized GPLVMs for Single Cell Transcriptomics Data.

Sarah Zhao, Aditya Ravuri, Vidhi Lalchand, Neil D. Lawrence

CoRR, 2024

Uncertainty as a Predictor: Leveraging Self-Supervised Learning for Zero-Shot MOS Prediction.

Aditya Ravuri, Erica Cooper, Junichi Yamagishi

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Dimensionality Reduction as Probabilistic Inference.

Aditya Ravuri, Francisco Vargas, Vidhi Lalchand, Neil D. Lawrence

CoRR, 2023

GAUCHE: A Library for Gaussian Processes in Chemistry.

Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Yuanqi Du, Samuel Stanton, Gary Tom, Bojana Rankovic, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Johannes Peter Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha A. Lee, Bingqing Cheng, Alán Aspuru-Guzik, Philippe Schwaller, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

GAUCHE: A Library for Gaussian Processes in Chemistry.

Ryan-Rhys Griffiths, Leo Klarner, Henry B. Moss, Aditya Ravuri, Sang Truong, Bojana Rankovic, Yuanqi Du, Arian R. Jamasb, Julius Schwartz, Austin Tripp, Gregory Kell, Anthony Bourached, Alex Chan, Jacob Moss, Chengzhi Guo, Alpha A. Lee, Philippe Schwaller, Jian Tang

CoRR, 2022

Ice Core Dating using Probabilistic Programming.

Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite, Will Tebbutt, Richard E. Turner, J. Scott Hosking, Neil D. Lawrence, Markus Kaiser

CoRR, 2022

Generalised Gaussian Process Latent Variable Models (GPLVM) with Stochastic Variational Inference.

Vidhi Lalchand, Aditya Ravuri, Neil D. Lawrence

CoRR, 2022

Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs.

Vidhi Lalchand, Aditya Ravuri, Emma Dann, Natsuhiko Kumasaka, Dinithi Sumanaweera, Rik G. H. Lindeboom, Shaista Madad, Sarah A. Teichmann, Neil D. Lawrence

Proceedings of the Machine Learning in Computational Biology, 21-22 November 2022, Online, 2022

Generalised GPLVM with Stochastic Variational Inference.

Vidhi Lalchand, Aditya Ravuri, Neil D. Lawrence

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022