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Ian Adelstein
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2020 – today
- 2024
- [c7]Charles Xu
, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter:
BLIS-Net: Classifying and Analyzing Signals on Graphs. AISTATS 2024: 4537-4545 - [c6]Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel
, Ian Adelstein, Smita Krishnaswamy:
Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CISS 2024: 1-6 - [i8]Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Chen Liu, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy:
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds. CoRR abs/2410.12779 (2024) - [i7]Elliott Abel, Peyton Crevasse, Yvan Grinspan, Selma Mazioud, Folu Ogundipe, Kristof Reimann, Ellie Schueler, Andrew J. Steindl, Ellen Zhang, Dhananjay Bhaskar, Siddharth Viswanath, Yanlei Zhang, Tim G. J. Rudner, Ian Adelstein, Smita Krishnaswamy:
Exploring the Manifold of Neural Networks Using Diffusion Geometry. CoRR abs/2411.12626 (2024) - 2023
- [c5]Tesfa Asmara, Dhananjay Bhaskar, Ian Adelstein, Smita Krishnaswamy, Michael Perlmutter:
Wire Before You Walk. ACSSC 2023: 714-716 - [c4]Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy:
Neural FIM for learning Fisher information metrics from point cloud data. ICML 2023: 9814-9826 - [c3]Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, Smita Krishnaswamy:
A Flow Artist for High-Dimensional Cellular Data. MLSP 2023: 1-6 - [c2]Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy:
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. NeurIPS 2023 - [i6]Guillaume Huguet, Alexander Tong, Edward De Brouwer, Yanlei Zhang, Guy Wolf, Ian Adelstein, Smita Krishnaswamy:
A Heat Diffusion Perspective on Geodesic Preserving Dimensionality Reduction. CoRR abs/2305.19043 (2023) - [i5]Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy:
Neural FIM for learning Fisher Information Metrics from point cloud data. CoRR abs/2306.06062 (2023) - [i4]Kincaid MacDonald, Dhananjay Bhaskar, Guy Thampakkul, Nhi Nguyen, Joia Zhang, Michael Perlmutter, Ian Adelstein, Smita Krishnaswamy:
A Flow Artist for High-Dimensional Cellular Data. CoRR abs/2308.00176 (2023) - [i3]Charles Xu, Laney Goldman, Valentina Guo, Benjamin Hollander-Bodie, Maedee Trank-Greene, Ian Adelstein, Edward De Brouwer, Rex Ying, Smita Krishnaswamy, Michael Perlmutter:
BLIS-Net: Classifying and Analyzing Signals on Graphs. CoRR abs/2310.17579 (2023) - [i2]Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong
, Guillaume Huguet, Guy Wolf, Maximilian Nickel
, Ian Adelstein, Smita Krishnaswamy:
Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CoRR abs/2312.04823 (2023) - 2022
- [c1]Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck, Ian Adelstein, Smita Krishnaswamy:
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. NeurIPS 2022 - [i1]Dhananjay Bhaskar, Kincaid MacDonald, Oluwadamilola Fasina, Dawson Thomas, Bastian Rieck
, Ian Adelstein, Smita Krishnaswamy:
Diffusion Curvature for Estimating Local Curvature in High Dimensional Data. CoRR abs/2206.03977 (2022)
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