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ORCIDAditya Ravuri
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2020 – today
- 2024
[c4]Aditya Ravuri, Erica Cooper, Junichi Yamagishi:
Uncertainty as a Predictor: Leveraging Self-Supervised Learning for Zero-Shot MOS Prediction. ICASSP Workshops 2024: 580-584- [i10]Sarah Zhao, Aditya Ravuri, Vidhi Lalchand, Neil D. Lawrence
:
Scalable Amortized GPLVMs for Single Cell Transcriptomics Data. CoRR abs/2405.03879 (2024) - [i9]Aditya Ravuri, Neil D. Lawrence:
Towards One Model for Classical Dimensionality Reduction: A Probabilistic Perspective on UMAP and t-SNE. CoRR abs/2405.17412 (2024) - [i8]Aditya Ravuri, Jen Muir, Neil D. Lawrence:
On Feature Learning for Titi Monkey Activity Detection. CoRR abs/2407.01452 (2024) - [i7]Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy:
The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. CoRR abs/2407.08086 (2024) - 2023
- [c3]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:
GAUCHE: A Library for Gaussian Processes in Chemistry. NeurIPS 2023 - [i6]Aditya Ravuri, Francisco Vargas, Vidhi Lalchand, Neil D. Lawrence:
Dimensionality Reduction as Probabilistic Inference. CoRR abs/2304.07658 (2023) - [i5]Aditya Ravuri, Erica Cooper, Junichi Yamagishi:
Uncertainty as a Predictor: Leveraging Self-Supervised Learning for Zero-Shot MOS Prediction. CoRR abs/2312.15616 (2023) - 2022
- [c2]Vidhi Lalchand, Aditya Ravuri, Neil D. Lawrence:
Generalised GPLVM with Stochastic Variational Inference. AISTATS 2022: 7841-7864 - [c1]Vidhi Lalchand, Aditya Ravuri, Emma Dann, Natsuhiko Kumasaka, Dinithi Sumanaweera, Rik G. H. Lindeboom, Shaista Madad, Sarah A. Teichmann, Neil D. Lawrence:
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs. MLCB 2022: 46-60 - [i4]Vidhi Lalchand, Aditya Ravuri, Neil D. Lawrence:
Generalised Gaussian Process Latent Variable Models (GPLVM) with Stochastic Variational Inference. CoRR abs/2202.12979 (2022) - [i3]Vidhi Lalchand, Aditya Ravuri, Emma Dann, Natsuhiko Kumasaka, Dinithi Sumanaweera, Rik G. H. Lindeboom, Shaista Madad, Sarah A. Teichmann, Neil D. Lawrence:
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs. CoRR abs/2209.06716 (2022) - [i2]Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite, Will Tebbutt, Richard E. Turner, J. Scott Hosking, Neil D. Lawrence, Markus Kaiser:
Ice Core Dating using Probabilistic Programming. CoRR abs/2210.16568 (2022) - [i1]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:
GAUCHE: A Library for Gaussian Processes in Chemistry. CoRR abs/2212.04450 (2022)
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