SELECTED PUBLICATIONS
Journal and Conference Papers
2024
The Selective G-Bispectrum and its Inversion: Applications to G-Invariant Networks
S Mataigne, J Mathe, S Sanborn, C Hillar, N Miolane
NeurIPS 2024
[paper]
Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems
F Acosta, F Dinc, W Redman, M Madhav, D Klindt, N Miolane
NeurIPS 2024
[paper]
Not so griddy: Internal representations of RNNs path integrating more than one agent
W Redman, F Acosta, S Acosta-Mendoza, N Miolane
NeurIPS 2024
[paper]
Unveiling cellular morphology: statistical analysis using a Riemannian elastic metric in cancer cell image datasets
W Li, A Prasad, N Miolane, K Dao Duc
Information Geometry, 2024
[paper]
Coded Computing Meets Quantum Circuit Simulation: Coded Parallel Tensor Network Contraction Algorithm
J Lee, S Gonzalez-Garcia, Z Zhang, H Jeong
ISIT 2024
[paper]
Fast Decision Boundary based Out-of-Distribution Detector
L Liu, Y Qin
ICML 2024
[paper]
Towards Interpretable Cryo-EM: Disentangling Latent Spaces of Molecular Conformations
DA Klindt, A Hyvarinen, A Levy, N Miolane, F Poitevin
Frontiers in Molecular Biosciences 2024
[paper]
Position Paper: Challenges and Opportunities in Topological Deep Learning
T Papamarkou, T Birdal, M Bronstein, G Carlsson, J Curry, Y Gao, M Hajij, R Kwitt, P Liò, PD Lorenzo, V Maroulas, N Miolane, F Nasrin, KN Ramamurthy, B Rieck, S Scardapane, MT Schaub, P Veličković, B Wang, Y Wang, G Wei, G Zamzmi
ICML 2024
[paper]
Initialization Matters for Adversarial Transfer Learning
A Hua, J Gu, Z Xue, N Carlini, E Wong, Y Qin
CVPR 2024
[paper]
Improving Robustness via Tilted Exponential Layer: A Communication-Theoretic Perspective
B Puranik, A Beirami, Y Qin, U Madhow
AISTATS 2024
[paper]
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting
X Zhang, S Li, X Yang, C Tian, Y Qin, LR Petzold
ICLR 2024
[paper]
Coded Computing for Fault-Tolerant Parallel QR Decomposition
QM Nguyen, I Weissburg, H Jeong
SIAM Conference on Applied Linear Algebra 2024
[paper]
2023
A General Framework for Robust G-Invariance in G-Equivariant Networks
S Sanborn, N Miolane
NeurIPS 2023
[paper]
Effective Robustness against Natural Distribution Shifts for Models with Different Training Data
Z Shi, N Carlini, A Balashankar, L Schmidt, CJ Hsieh, A Beutel, Y Qin
NeurIPS 2023
[paper]
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation
A Balashankar, X Wang, Y Qin, B Packer, N Thain, E Chi, J Chen, et al.
EMNLP 2023
[paper]
What are effective labels for augmented data? improving calibration and robustness with autolabel
Y Qin, X Wang, B Lakshminarayanan, EH Chi, A Beutel
2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
[paper]
Differentially Private Secure Multiplication: Hiding Information in the Rubble of Noise
VR Cadambe, H Jeong, FP Calmon
IEEE International Symposium on Information Theory (ISIT) 2023
[paper]
Septins Regulate Border Cell Shape and Surface Geometry ownstream of Rho
AM Gabbert, JP Campanale, JA Mondo, NP Mitchell, A Myers, S Streichan, N Miolane, D Montell
Developmental Cell 2023
[paper]
Orthogonal Outlier Detection and Dimension Estimation for Improved MDS Embedding of Biological Datasets
W Li, J Mirone, A Prasad, N Miolane, C Legrand, K Dao Duc
Frontiers in Bioinformatics 2023
[paper]
Using an Elastic Metric for Statistical Analysis of Tumor Cell Shape Heterogeneity
W Li, A Prasad, N Miolane, K Dao Duc
Geometric Science of Information 2023
[paper]
Group Equivariant Sparse Coding
C Shewmake, N Miolane, B Olshausen
Geometric Science of Information 2023
[paper]
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices
S Utpala, P Vepakomma, N Miolane
Transactions of Machine Learning Research (TMLR) 2023
[paper]
Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy
C Donnat, A Levy, F Poitevin, ED Zhong, N Miolane
Journal of Structural Biology 2023
[paper]
Introduction to Riemannian Geometry and Geometric Statistics: from theory to implementation with Geomstats
N Guigui, N Miolane, X Pennec, et al.
Journal of Foundations and Trends in Machine Learning 2023
[paper]
2022 and before
Defining an Action of SO(d)-Rotations on Projections of d-Dimensional Objects: Applications to Pose Inference with Geometric VAEs
N Legendre, KD Duc, N Miolane
GRETSI Conference (2022)
[paper]
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images
A Levy, F Poitevin, J Martel, Y Nashed, A Peck, N Miolane, D Ratner, M Dunne, G Wetzstein
ECCV 2022
[paper]
Parametric Information Geometry with the Package Geomstats
A Le Brigant, J Deschamps, A Collas, N Miolane
Transactions of Mathematical Software (TOMS) 2022
[paper]
Biological Shape Analysis with Geometric Statistics and Learning
S Utpala, N Miolane
Oberwolfach Snapshots 2022
[paper]
PirouNet: Creating Dance through Artist-Centric Deep Learning
M Papillon, M Pettee, N Miolane
EAI ArtsIT Conference. Best Paper Award (Oral)
[paper]
Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection
W Alghamdi, H Hsu, H Jeong, H Wang, P Michalak, S Asoodeh, F Calmon
NeurIPS 2022
[paper]
Fairness Without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values
H Jeong, H Wang, FP Calmon
AAAI 2022
[paper]
Are Vision Transformers Robust to Patch Perturbations?
J Gu, V Tresp, Y Qin
ECCV 2022
[paper]
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers
J Zhao, X Wang, Y Qin, J Chen, KW Chang
EMNLP 2022 - Findings
[paper]
Understanding and improving robustness of vision transformers through patch-based negative augmentation
Y Qin, C Zhang, T Chen, B Lakshminarayanan, A Beutel, X Wang
NeurIPS 2022
[paper]
Improving Calibration through the Relationship with Adversarial Robustness
Y Qin, X Wang, A Beutel, E Chi
NeurIPS 2021
[paper]
ϵ-Approximate Coded Matrix Multiplication Is Nearly Twice as Efficient as Exact Multiplication
H Jeong, A Devulapalli, VR Cadambe, FP Calmon
IEEE Journal on Selected Areas in Information Theory 2021
[paper]
Coded QR Decomposition
QM Nguyen, H Jeong, P Grover
ISIT 2020
[paper]
Differentially private distributed matrix multiplication: Fundamental accuracy-privacy trade-off limits
A Devulapalli, VR Cadambe, FP Calmon, H Jeong
ISIT 2020
[paper]
Geomstats: A Python Package for Riemannian Geometry in Machine Learning
N Miolane, N Guigui, A Le Brigant, J Mathe, B Hou, Y Thanwerdas, et al.
The Journal of Machine Learning Research 21 (1), 9203-9211, 2020 / [paper] [code]
Learning Weighted Submanifolds With Riemannian Variational Autoencoders
N Miolane, S Holmes
CVPR 2020
[paper]
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation
T Wang, X Wang, Y Qin, B Packer, K Li, J Chen, A Beutel, E Chi
EMNLP 2020
[paper]
Introduction to Geometric Learning in Python with Geomstats
N Miolane, N Guigui, H Zaatiti, C Shewmake, H Hajri, D Brooks, et al.
SciPy Conference on Scientific Computing in Python 2020
[paper]
Bias on Estimation in Quotient Space and Correction Methods
N Miolane, L Devilliers, X Pennec
Elsevier 2020
[paper]
Intelligence-based Medicine
A Chang et al. (including N Miolane)
Elsevier 2020
[book]
Detecting and Diagnosing Adversarial Images with Class-conditional Capsule Reconstructions
Y Qin, N Frosst, S Sabour, C Raffel, G Cottrell, G Hinton
ICLR 2020
[paper]
Imperceptible, Robust and Targeted Adversarial Examples for Automatic Speech Recognition
Y Qin, N Carlini, I Goodfellow, G Cottrell, C Raffel
ICML 2019
[paper]
On the Optimal Recovery Threshold of Coded Matrix Multiplication
S Dutta, M Fahim, F Haddadpour, H Jeong, V Cadambe, P Grover
IEEE Transactions on Information Theory 66 (1), 278-301, 2019
[paper]
Hierarchical Cellular Automata for Visual Saliency
Y Qin, M Feng, H Lu, GW Cottrell
International Journal of Computer Vision 2018
[paper]
Autofocus Layer for Semantic Segmentation
Y Qin, K Kamnitsas, S Ancha, J Nanavati, G Cottrell, A Criminisi, A Nori
MICCAI Conference on Medical Image Computing and Computer Assisted Intervention 2018
[paper]
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
B Hou, N Miolane, B Khanal, MCH Lee, A Alansary, S McDonagh, et al.
MICCAI Conference on Medical Image Computing and Computer Assisted Intervention 2018
[paper]
Topologically Constrained Template Estimation
N Miolane, S Holmes, X Pennec
SIAM Journal on Applied Algebra and Geometry 2018
[paper]
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction
Y Qin , D Song, H Chen, W Cheng, G Jiang, G Cottrell
International Joint Conference on Artificial Intelligence (IJCAI) 2017
[paper]
Template Shape Estimation in Computational Anatomy
N Miolane, S Holmes, X Pennec
SIAM Journal of Imaging Science 2017
[paper]
Biased Estimators on Quotient spaces
N Miolane, X Pennec
Conference on Geometric Sciences of Information (GSI) 2015
[paper]
Saliency Detection via Cellular Automata
Y Qin, H Lu, Y Xu, H Wang
CVPR 2015
[paper]
Computing Bi-Invariant Pseudo-Metrics on Lie Groups
N Miolane, X Pennec
Entropy 2015
[paper]
Statistics on Lie Groups for Computational Anatomy
N Miolane, B khanal
MICCAI 2014
Analyse Biométrique de l'Anneau Pelvien en 3 Dimensions
H Darmanté, B Bugnas, RB De Dompsure, L Barresi, N Miolane, et al.
Journal Revue de Chirurgie Orthopédique et Traumatologique 2014
[paper]
Workshop Papers
2024
On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets?
A Myers, N Miolane
CVPRW L3D-IVU: Learning with Limited Labelled Data for Image and Video Understanding, 2024
2023
Relating Representational Geometry to Cortical Geometry in the Visual Cortex
F Acosta, C Conwell, S Sanborn, D Klindt, N Miolane
NeurIPS Workshop on Unifying Representations in Neural Models, 2023
[paper]
ICML 2023 Topological Deep Learning Challenge: Design and Results
M Papillon, N Miolane, et al.
2nd Annual Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), ICML, 2023
[paper]
Visual Scene Representation with Hierarchical Equivariant Sparse Coding
CA Shewmake, D Buracas, H Lillemark, J Shin, EJ Bekkers, N Miolane, Bruno Olshausen
NeurIPS 2023 Workshop on Symmetry and Geometry in Neural Representations
[paper]
Geodesic Regression Characterizes 3D Shape Changes in the Female Brain During Menstruation
A Myers, C Taylor, E Jacobs, N Miolane
ICCV 2023 Workshop on Computer Vision for Automated Medical Diagnosis
[paper]
CryoChains: Heterogeneous Reconstruction of Molecular Assembly of Semi-flexible Chains from Cryo-EM Images
B Koo, J Martel, A Peck, A Levy, F Poitevin, N Miolane
ICML CompBio Workshop 2023
[paper]
Quantifying Extrinsic Curvatures of Neural Manifolds
F Acosta, S Sanborn, KD Duc, M Madhav, N Miolane
CVPR Workshop on TAG in Pattern Recognition with Applications (TAG-RPA) 2023
[paper]
Robust Deep Learning via Layerwise Tilted Exponentials
B Puranik, A Beirami, Y Qin, U Madhow
The Second Workshop on New Frontiers in Adversarial Machine Learning
[paper]
2022 and before
Heterogeneous Reconstructions of Deformable Models in Cryo-Electron Microscopy
Y Nashed, A Peck, J Martel, A Levy, B Koo, G Wetzstein, N Miolane, D Ratner, F Poitevin
NeurIPS Workshop of Machine Learning for Structural Biology (MLSB) 2022
[paper]
Testing Geometric Representation Hypotheses from Simulated Place Cells Recordings
T Niederhauser, A Lester, N Miolane, KD Duc, MS Madhav
NeurIPS Workshop of Machine Learning for Structural Biology (MLSB) 2022
[paper]
Regression-Based Elastic Metric Learning on Shape Spaces of Elastic Curves
A Myers, N Miolane
NeurIPS Workshop on Learning Meaningful Representations of Life 2022
[paper]
Challenge for Computational Geometry and Topology: Design and Results
A Myers, S Utpala, S Talbar, S Sanborn, C Shewmake, C Donnat, J Mathe, R Sonthalia, X Cui, T Szwagier, A Pignet, A Bergsson, S Hauberg, D Nielsen, S Sommer, D Klindt, E Hermansen, M Vaupel, B Dunn, J Xiong, N Aharony, I Pe’er, F Ambellan, M Hanik, E Nava-Yazdani, C von Tycowicz, N Miolane
ICLR Geometrical and Topological Representation Learning 2022
[paper]
Intentional Choreography with Semi-Supervised Recurrent Variational Autoencoders
M Papillon, M Pettee, N Miolane
NeurIPS Workshop of Creativity and Design 2022
[paper]
Challenge for Computational Geometry & Topology: Design and Results
N Miolane, M Caorsi, U Lupo, M Guerard, N Guigui, J Mathe, et al.
ICLR Workshop on Geometrical and Topologic Representation Learning 2021
[paper]
Who gets the benefit of the doubt? racial bias in machine learning algorithms applied to secondary school math education
H Jeong, MD Wu, N Dasgupta, M Médard, F Calmon
NeurIPS 2021 Workshop: Math AI for Education: Bridging the Gap Between Research and Smart Education
[paper]
Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
N Miolane, F Poitevin, YT Li, S Holmes
CVPR Workshop on Computer Vision for Microscopy Imaging 2020
[paper]
A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses
C Donnat, N Miolane, F Bunbury, J Kreindler
NeurIPS Workshop on Machine Learning for Health 2020
1st Prize: C3.ai Grand Covid Challenge (100,000$)
[paper]
Exploring Cryo-EM Latent Space with Variational Autoencoders
N Miolane, F Poitevin, S Holmes
Stanford Bio-X Workshop on Cryo-Electron Microscopy 2019
Convenience Tools to Explore Variability in Cryo-EM Data
F Poitevin, YT Li, N Miolane, C Gati, M Levitt
Stanford Bio-X Workshop on Cryo-Electron Microscopy 2019
PVNet: A LRCN Architecture for Spatio-Temporal Photovoltaic Power Forecasting from Numerical Weather Prediction
J Mathe, N Miolane, N Sebastien, J Lequeux
ICML Workshop on AI for Climate Change 2019
[paper]
Toward a Unified Geometric Bayesian Framework for Template Estimation in Computational Anatomy
N Miolane, X Pennec, S Holmes
ISBA World Meeting of the International Society for Bayesian Analysis 2016
[paper]
Mathematical Structures for Extending 2D Neurogeometry to 3D Image Processing
N Miolane, X Pennec
MICCAI Workshop of Medical Computer Vision 2015
[paper]
Statistics on Lie Groups
N Miolane, X Pennec
MaxEnt Workshop on Bayesian Inference and Maximum Entropy Methods 2014 (Oral)
[paper]
Statistics on Lie Groups: Can We Obtain a Consistent Framework with Pseudo-Riemannian Metrics?
N Miolane
Institut Henri Poincaré Workshop on Geometrical Models in Vision 2014
Preprints
2024
An efficient algorithm for the Riemannian logarithm on the Stiefel manifold for a family of Riemannian metrics
S Mataigne, R Zimmermann, N Miolane
[arXiv preprint]
TopoX: a suite of Python packages for machine learning on topological domains
M Hajij, M Papillon, F Frantzen, J Agerberg, I AlJabea, R Ballester, C Battiloro, G Bernárdez, T Birdal, A Brent, P Chin, S Escalera, OH Gardaa, G Gopalakrishnan, D Govil, J Hoppe, MR Karri, J Khouja, M Lecha, N Livesay, J Meißner, S Mukherjee, A Nikitin, T Papamarkou, KN Ramamurthy, P Rosen, A Salatiello, SN Samaga, MT Schaub, L Scofano, I Spinelli, L Telyatnikov, Q Truong, R Walters, M Yang, O Zaghen, G Zamzmi, A Zia, N Miolane
[arXiv preprint]
A Survey on Data Selection for Language Models
A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert, X Wang, N Muennighoff, B Hou, L Pan, H Jeong, C Raffel, S Chang, T Hashimoto, WY Wang
[arXiv preprint]
2023
Identifying Interpretable Visual Features in Artifical and Biological Neural Systems
D Klindt, S Sanborn, F Acosta, F Poitevin, N Miolane
[arXiv preprint]
Unsupervised learning of structural variability in cryo-EM data using normal mode analysis of deformable atomic models
Y Nashed, J Martel, A Peck, A Levy, G Wetzstein, N Miolane, D Ratner, F Poitevin
Submitted to Nature Methods 2023
Topological Deep Learning: Going Beyond Graph Data
M Hajij, G Zamzmi, T Papamarkou, N Miolane, A Guzmán-Sáenz, et al.
Submitted to JMLR: Journal of Machine Learning Research 2023
[paper]
Architectures of Topological Deep Learning: A Survey on Topological Neural Networks
M Papillon, S Sanborn, M Hajij, N Miolane
Submitted to PAMI: Transactions of Pattern Analysis and Machine Intelligence 2023
[arXiv preprint]
Probabilistic Riemannian Functional Map Synchronization for 3D Shape Correspondence
F Huq, A Dey, S Yusuf, D Bazazian, T Birdal, N Miolane
Submitted to Transactions of Machine Learning Research (TMLR) 2023
[paper]
Detecting Out-of-Distribution Through the Lens of Neural Collapse
L Liu, Y Qin
[arXiv preprint]
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning
A Balashankar, X Ma, A Sinha, A Beirami, Y Qin, J Chen, A Beutel
[arXiv preprint]
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
J Gu, Z Han, S Chen, A Beirami, B He, G Zhang, R Liao, Y Qin, V Tresp, et al.
[arXiv preprint]
Towards Robust Prompts on Vision-Language Models
J Gu, A Beirami, X Wang, A Beutel, P Torr, Y Qin
[arXiv preprint]
Training deep Boltzmann networks with sparse Ising machines
S Niazi, NA Aadit, M Mohseni, S Chowdhury, Y Qin, KY Camsari
[arXiv preprint]
2022 and before
Higher-Order Attention Networks
M Hajij, G Zamzmi, T Papamarkou, N Miolane, A Guzmán-Sáenz, KN Ramamurthy, et al.
[arXiv preprint]
Deflecting Adversarial Attacks
Y Qin, N Frosst, C Raffel, G Cottrell, G Hinton
[arXiv preprint] 2020
Evaluation Methodology for Attacks against Confidence Thresholding Models
I Goodfellow, Y Qin, D Berthelot
[prepreint] 2018