S. Manley, J. M. Gillette, G. H. Patterson, H. Shroff, H. F. Hess et al., High-density mapping of single-molecule trajectories with photoactivated localization microscopy, Nature Methods, vol.5, issue.2, pp.155-157, 2008.

G. Giannone, E. Hosy, F. Levet, A. Constals, K. Schulze et al., Dynamic Superresolution Imaging of Endogenous Proteins on Living Cells at Ultra-High Density, Biophysical Journal, vol.99, issue.4, pp.1303-1310, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00661871

J. Meier, C. Vannier, A. Sergé, A. Triller, and D. Choquet, Fast and reversible trapping of surface glycine receptors by gephyrin, Nature Neuroscience, vol.4, issue.3, pp.253-260, 2001.

J. Elf, G. Li, and X. S. Xie, Probing Transcription Factor Dynamics at the Single-Molecule Level in a Living Cell, Science, vol.316, issue.5828, pp.1191-1194, 2007.

R. Das, C. W. Cairo, and D. Coombs, A Hidden Markov Model for Single Particle Tracks Quantifies Dynamic Interactions between LFA-1 and the Actin Cytoskeleton, PLoS Computational Biology, vol.5, issue.11, p.e1000556, 2009.

P. Pierobon, S. Achouri, S. Courty, A. R. Dunn, J. A. Spudich et al., Velocity, Processivity, and Individual Steps of Single Myosin V Molecules in Live Cells, Biophysical Journal, vol.96, issue.10, pp.4268-4275, 2009.
URL : https://hal.archives-ouvertes.fr/hal-01138979

J. Masson, D. Casanova, S. Türkcan, G. Voisinne, M. R. Popoff et al., Inferring Maps of Forces inside Cell Membrane Microdomains, Physical Review Letters, vol.102, issue.4, p.48103, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00811680

A. V. Weigel, B. Simon, M. M. Tamkun, and D. Krapf, Ergodic and nonergodic processes coexist in the plasma membrane as observed by single-molecule tracking, Proceedings of the National Academy of Sciences, vol.108, issue.16, pp.6438-6443, 2011.

N. Hoze, D. Nair, E. Hosy, C. Sieben, S. Manley et al., Heterogeneity of AMPA receptor trafficking and molecular interactions revealed by superresolution analysis of live cell imaging, Proceedings of the National Academy of Sciences, vol.109, issue.42, pp.17052-17057, 2012.

D. Nair, E. Hosy, J. D. Petersen, A. Constals, G. Giannone et al., Super-Resolution Imaging Reveals That AMPA Receptors Inside Synapses Are Dynamically Organized in Nanodomains Regulated by PSD95, Journal of Neuroscience, vol.33, issue.32, pp.13204-13224, 2013.

C. G. Specht, I. Izeddin, P. C. Rodriguez, M. El beheiry, P. Rostaing et al., Quantitative Nanoscopy of Inhibitory Synapses: Counting Gephyrin Molecules and Receptor Binding Sites, Neuron, vol.79, issue.2, pp.308-321, 2013.

F. Persson, M. Lindén, C. Unoson, and J. Elf, Extracting intracellular diffusive states and transition rates from single-molecule tracking data, Nature Methods, vol.10, issue.3, pp.265-269, 2013.

J. Masson, P. Dionne, C. Salvatico, M. Renner, C. G. Specht et al., Mapping the Energy Landscapes of the Glycine Receptor in the Post-Synaptic Neuronal Membrane, Biophysical Journal, vol.104, issue.2, p.498a, 2013.

C. Manzo and M. F. Garcia-parajo, A review of progress in single particle tracking: from methods to biophysical insights, Reports on Progress in Physics, vol.78, issue.12, p.124601, 2015.

N. Monnier, Z. Barry, H. Y. Park, K. Su, Z. Katz et al., Inferring transient particle transport dynamics in live cells, Nature Methods, vol.12, issue.9, pp.838-840, 2015.

E. J. Akin, L. Solé, B. Johnson, M. E. Beheiry, J. Masson et al., Single-Molecule Imaging of Na v 1.6 on the Surface of Hippocampal Neurons Reveals Somatic Nanoclusters, Biophysical Journal, vol.111, issue.6, pp.1235-1247, 2016.

T. Sungkaworn, M. Jobin, K. Burnecki, A. Weron, M. J. Lohse et al., Single-molecule imaging reveals receptor?G protein interactions at cell surface hot spots, Nature, vol.550, issue.7677, pp.543-547, 2017.

A. Remorino, S. De-beco, F. D. Cayrac, F. Di-federico, G. Cornilleau et al., Gradients of Rac1 Nanoclusters Support Spatial Patterns of Rac1 Signaling, Cell Reports, vol.21, issue.7, pp.1922-1935, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01637091

D. Holcman, P. Parutto, J. E. Chambers, M. Fantham, L. J. Young et al., Single particle trajectories reveal active endoplasmic reticulum luminal flow, Nature Cell Biology, vol.20, issue.10, pp.1118-1125, 2018.

C. Floderer, J. Masson, E. Boilley, S. Georgeault, P. Merida et al., Author Correction: Single molecule localisation microscopy reveals how HIV-1 Gag proteins sense membrane virus assembly sites in living host CD4 T cells, Scientific Reports, vol.8, issue.1, p.16283, 2018.

I. Sgouralis and S. Pressé, An Introduction to Infinite HMMs for Single-Molecule Data Analysis, Biophysical Journal, vol.112, issue.10, pp.2021-2029, 2017.

N. Hoze and D. Holcman, Recovering a stochastic process from super-resolution noisy ensembles of single-particle trajectories, Physical Review E, vol.92, issue.5, p.52109, 2015.

D. Holcman, N. Hoze, and Z. Schuss, Analysis and Interpretation of Superresolution Single-Particle Trajectories, Biophysical Journal, vol.109, issue.9, pp.1761-1771, 2015.

M. E. Beheiry, M. Dahan, and J. Masson, InferenceMAP: mapping of single-molecule dynamics with Bayesian inference, Nature Methods, vol.12, issue.7, pp.594-595, 2015.

E. F. Koslover, C. K. Chan, and J. A. Theriot, Disentangling Random Motion and Flow in a Complex Medium, Biophysical Journal, vol.110, issue.3, pp.700-709, 2016.

A. Frishman and P. Ronceray, Learning Force Fields from Stochastic Trajectories, Physical Review X, vol.10, issue.2, 2020.

H. Robbins and S. Monro, A Stochastic Approximation Method, The Annals of Mathematical Statistics, vol.22, issue.3, pp.400-407, 1951.

J. C. Spall, Introduction to Stochastic Search and Optimization, 2003.

D. P. Kingma and M. Welling, An Introduction to Variational Autoencoders, 2019.

M. Welling, M. Rosen-zvi, and Y. W. Teh, Approximate inference by Markov chains on union spaces, Twenty-first international conference on Machine learning - ICML '04, pp.681-688, 2004.

J. C. Chang, P. Fok, and T. Chou, Bayesian Uncertainty Quantification for Bond Energies and Mobilities Using Path Integral Analysis, Biophysical Journal, vol.109, issue.5, pp.966-974, 2015.

G. Hummer and I. G. Kevrekidis, Coarse molecular dynamics of a peptide fragment: Free energy, kinetics, and long-time dynamics computations, The Journal of Chemical Physics, vol.118, issue.23, pp.10762-10773, 2003.

A. S. Serov, F. Laurent, C. Floderer, K. Perronet, C. Favard et al., Statistical Tests for Force Inference in Heterogeneous Environments, Scientific Reports, vol.10, issue.1, 2020.
URL : https://hal.archives-ouvertes.fr/pasteur-02865729

. Masson, Robust inference of forces in heterogeneous environments, 2019.

R. E. Kass and A. E. Raftery, Bayes Factors, Journal of the American Statistical Association, vol.90, issue.430, pp.773-795, 1995.

G. Peyré, Mathematical Foundations of Data Sciences

H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems, Regularization of inverse problems, vol.375, 1996.

W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, The art of scientific computing, 2007.

T. Savin and P. S. Doyle, Static and Dynamic Errors in Particle Tracking Microrheology, Biophysical Journal, vol.88, issue.1, pp.623-638, 2005.

C. L. Vestergaard, P. C. Blainey, and H. Flyvbjerg, Optimal estimation of diffusion coefficients from single-particle trajectories, Physical Review E, vol.89, issue.2, p.22726, 2014.

A. J. Berglund, Statistics of camera-based single-particle tracking, Physical Review E, vol.82, issue.1, p.11917, 2010.

C. L. Vestergaard, Optimizing experimental parameters for tracking of diffusing particles, Physical Review E, vol.94, issue.2, p.22401, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01144950