Lab Meeting Archives

Spring 2024

Date	Presenter	Authors	Paper & Blurb
01/01	New Year's Day	The Inexorable Flow of Time et al
01/08	Liz	Tang et al.	Dynamic behaviour restructuring mediates dopamine-dependent credit assignment
01/15	MLK Day
01/22	Labstravaganza	Group 2
01/29	Trevor	Abbaspourazad et al.	Dynamical flexible inference of nonlinear latent factors and structures in neural population activity
02/05	Labstravaganza	Group 1
02/12	David	Duong et al.	Adaptive whitening of Neural populations by Gain-modulated Interneurons
02/19	Labstravaganza	Group 2
02/26	Scott	Tsai et al.	Multimodal Transformer for Unaligned Multimodal Language Sequences (https://arxiv.org/pdf/1906.00295.pdf)
03/04	Cosyne	John, in Portugal
03/11	Pranjal	Me	Dissertation D:
03/18	Raphael	Me	Dissertation Practice
03/25	Labstravaganza	Group 1
04/01	Kevin	Him	Dissertation (actual)
04/08	Miles	Timothy Doeyeon Kim et al.	Flow-field inference from neural data using deep recurrent networks, Poisson latent neural differential equations: latent dynamical systems for spiking data
04/15	Labstravaganza	Group 1
04/22	Daniela	Kadkhodaie & Simoncelli, Kadkhodaie et al.	Solving Linear Inverse Problems Using the Prior Implicit in a Denoiser, Generalization in Diffusion Models Arises from Geometry-Adaptive Harmonic Representations
04/29	Labstravaganza	Group 2
05/06	Seth	Polanía, Woodford, & Ruff	Efficient coding of subjective value
05/13	Labstravaganza	Group 1

Fall 2023

Date	Presenter	Authors	Paper & Blurb
08/28	Pranjal
09/04	Labor Day
09/11	David	Practice Talk
09/18	Research roundup	Group 1
09/25	Scott	Timothy A. Krausz, Alison E. Comrie,Ari E. Kahn, Loren M. Frank,Nathaniel D. Daw, Joshua D. Berke	Dual credit assignment processes underlie dopamine signals in a complex spatial environment Authors investigate how expectations of future reward are updated through experience. In rats traversing a complex maze, they show that nucleus accumbens dopamine scales with reward expectation from each location. This expectation signal propagates between adjacent spatial locations and is also inferred using knowledge of maze structure.
10/02	Research roundup	Group 2
10/09	Raphael	Karayanidis et al., 2023	Jointly modeling behavioral and EEG measures of proactive control in task switching
10/16	Research roundup	Group 1
10/23	Miles	Duncker et al.	Learning interpretable continuous-time models of latent stochastic dynamical systems, bonus background: Variational inference for diffusion processes, bonus foreground: State estimation of a physical system with unknown governing equations
10/30	Research roundup	Group 2
11/06	Daniela	Me + Bunch of other (MUCH SMARTER) people	(Deep?) Dive into Diffusion Based Model's SDE-ODE "Duality"
11/13	Research roundup	Group 1
11/20	Thanksgiving break (starts Tuesday but who's counting?)
11/27	Seth
12/04	Research roundup	Group 2
12/11	Kevin	Schulz et al. (2023)	Metacognitive Computations for Information Search: Confidence in Control
12/18	Research roundup	Group 1
12/25	You there, student, what day is it today?	Why, Christmas Day!	Bring me the biggest equation you can find!

Lab meeting schedule Summer 2023

Date	Presenter	Authors	Paper & Blurb
05/22	Seth	Seth Hill (no relation); David E. Broockman & Joshua L. Kalla	Learning together slowly: Bayesian learning about political facts; Consuming cross-cutting media causes learning and moderates attitudes: A field experiment with Fox News viewers
05/29	N/A
06/05	Kevin
06/12	Research roundup	Group 1
06/19	Juneteenth
06/26	Research roundup	Group 2
07/03	July (4-1)th
07/10	Research roundup	Group 1
07/17	Maria & Sangkyu
07/24	Research roundup	Group 2
07/31	Liz	Toutounji et al., 2023	Learning the sound inventory of a complex vocal skill via an intrinsic reward
08/07	Research roundup	Group 1
08/14	Trevor	Anqi Zhang and co	Ultraflexible endovascular probes for brain recording through micrometer-scale vasculature
08/21	Research roundup	Group 2

Lab Meeting Schedule Spring 2023

Date	Presenter	Authors	Paper & Blurb
01/09	Seth	Me!	Research update
01/16	MLK Day
01/23	Miles	ALSO me!	Research update ALSO
01/30	Trevor	Sylwestrak EL et al, 2022	Cell-type-specific population dynamics of diverse reward computations
02/06	Raphael	Rmus, Zou, & Collins, 2022	Choice Type Impacts Human Reinforcement Learning
02/13	Pranjal	Markowitz, ..., Datta, 2023	Spontaneous behaviour is structured by reinforcement without explicit reward
02/20	Daniela	Nair et al., 2023	An approximate line attractor in the hypothalamus encodes an aggressive state
02/27	Kevin	Ma, Sun & Zou (2023)	A spectral method for assessing and combining multiple data visualizations
03/06	Seth	Various and sundry	The Sad Truth about Happiness Scales; How Threatening Are Transformations of Happiness Scales to Subjective Wellbeing Research?; The scientific value of numerical measures of human feelings
03/13	Spring Break
03/20	Liz	Me :)	Practice Student Seminar Talk
03/27	Labwide Research Roundup!
04/03	Trevor	Ana M.G. Manea, Anna Zilverstand, Benjamin Hayden, Jan Zimmermann	Neural timescales reflect behavioral demands in freely moving rhesus macaques
04/10	Yaohui Ding		Some Methodological Considerations on the Application of PLS-DA to Task fMRI Data Classification
04/17	Raphael	Jaffe, Poldrack, Schafer, & Bissett 2023	Modelling human behaviour in cognitive tasks with latent dynamical systems
04/24	Pranjal	A bunch	Something about sparsity
05/01	Miles	Me!	Practice Prelim Presentation (P^3)
05/08	Daniela	Welling et al., 2023	Latent Traversals in Generative Models as Potential Flows
05/15	John	Also John	AMA

Lab Meeting Schedule Fall 2022

Date	Presenter	Authors	Paper & Blurb
08/22	Liz	Jia et al., 2022	Selfee, self-supervised features extraction of animal behaviors
08/29	Miles	Me + Chen et al. (2020), Chen & He (2020), Tian et al. (2021)	Project updates, similarity based learning (Representation learning with contrastive predictive coding, Exploring simple siamese representation learning Understanding self-supervised learning dynamics without contrastive pairs)
09/05	Labor Day
09/12	Trevor	myself	Committee Meeting Practice
09/19	John	all of you	talk practice
09/26	Raphael	Me	Project updates/ideas for modeling cognitive stability-flexibility
10/03	Na Young	myself	How I manage code/data/meeting notes
10/10	Fall Break
10/17	Pranjal	Triplett et al., 2022	Rapid learning of neural circuitry from holographic ensemble stimulation enabled by model-based compressed sensing
10/24	Seth	Ebitz et al. x2	Exploration Disrupts Choice-Predictive Signals and Alters Dynamics in Prefrontal Cortex, Rules warp feature encoding in decision-making circuits
10/31	Daniela	Me + Some other folks	Prelim Oral Practice!
11/7	Na Young		Dissertation Practice (2pm)
11/14	John		Soft skills for theorists
11/21	Na Young		Dissertation Celebration!
11/28	Liz	Various	Thanksgiving Dinner Table Conversations: Equality in STEM
12/05	Kevin	Peter Dayan	Metacognitive Information Theory
12/12	Na Young	Dr. Na Young	Career Session!! Transition to theoretical/computational neuro!
12/19	Everyone was gone
12/26	Boxing Day		Boxing, presumably

Lab Meeting Presentation Schedule Summer 2022

Date	Presenter	Authors	Paper & Blurb
05/09	Seth	Ashwood et al	Mice alternate between discrete strategies during perceptual decision-making
05/16	Liz	Schneider, Lee, and Mathis, 2022	Learnable latent embeddings for joint behavioral and neural analysis
05/23	Miles	Casale et al 2018, Jazbec et al. 2020,Fortuin et al. 2020	GAUSSIAN PROCESS VAE WOWOWOWOWOWOWOW: Gaussian Process Prior Variational Autoencoders, Scalable Gaussian Process Variational Autoencoders, GP-VAE: Deep Probabilistic Time Series Imputation
05/30	Memorial Day
06/06	Trevor
06/13	Raphael	Flesch et al., 2022	Orthogonal representations for robust context dependent task performance in brains and neural networks
06/20	Juneteenth holiday
06/27	Achint	Lowe et al, Lin et al	Complex-Valued Autoencoders for Object Discovery, Variational Interpretable Learning from Multi-view Data
07/04	4th of July
07/11	Preston Jiang	Jiang and Rao	Dynamic Predictive Coding: A New Model of Hierarchical Sequence Learning and Prediction in the Cortex
07/18	Daniela	Multiple (see links)	Diffusion Models Stravaganza! Deep Unsupervised Learning using Nonequilibrium Thermodynamics; Modeling by estimating Gradients of the Data Distribution; Score-Based Generative Modeling through SDEs; Improved techniques for training score-based generative models
07/25	Seth	A bunch of economists	Strategic Information Transmission; Overcommunication in strategic information transmission games; Bayesian Persuasion
08/01	Pranjal	Mudrik, Chen, et al. 2022; Song et al. 2022	Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics; Modeling and Inference Methods for Switching Regime-Dependent Dynamical Systems with Multiscale Neural Observations
08/08	Anne		Efficient decoding of large-scale neural population responses with Gaussian-process multiclass regression
08/15	Kevin	Mitra Javadzadeh & Sonja B. Hofer	Dynamic causal communication channels between neocortical areas

Lab Meeting Presentation Schedule Spring 2022

Date	Presenter	Authors	Paper & Blurb
01/10	Seth	McDiarmid et al., 2021	Psychologists update their beliefs about effect sizes after replication studies
01/17	MLK Day
01/24	Anne	Dubreuil et al., bioRxiv, 2021	The role of population structure in computations through neural dynamics. See also: Probing the relationship between linear dynamical systems and low-rank recurrent neural network models
01/31	Trevor	Practice Talk
02/07	Ziyi
02/14	Nishanth
02/21	Achint	Zhang et. al., 2022	Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
02/28	Brayan	Past research and Bolding & Franks, 2018	Recurrent cortical circuits implement concentration-invariant odor coding
03/07	Spring Break
03/14	Kevin	Lepperød et al. 2022	Inferring causal connectivity from pairwise recordings and optogenetics
03/21	Raphael	Russin et al., 2022	A neural network model of continual learning with cognitive control
03/28	Miles	Solin, Tamir, & Verma (2021), Vahdat, Kreis, & Kautz (2021), Song et al. (2021)	Practice Qual: Scalable Inference in SDEs by Direct Matching of the FPK Equation, Score-based Generative Modeling in Latent Space, Score-Based Generative Modeling Through Stochastic Differential Equations
04/04	Pranjal	Bordelon & Pehlevan (2022)	Population codes enable learning from few examples by shaping inductive bias
04/11	Daniela	De Bortoli et al. (2021)	Diffusion Schrodinger Bridges with Applications to Score-Based Generative Modeling
04/18	Na Young	Practice Talk
04/25	Yule	Mitochondria are the Powerhouse of the Cell

(Semi-Virtual) Lab Meeting Presentation Schedule Fall 2021

Date	Presenter	Authors	Paper & Blurb
08/30	Kevin	Morris et al., 2019	Generating options and choosing between them rely on distinct forms of value representation
09/13	Miles	Burns et al. 2021, Chen et al. 2020	Unsupervised Disentanglement without Autoencoding: Pitfalls and Future Directions, A Simple Framework for Contrastive Learning of Visual Representations
09/27	Trevor	Peterson et al., 2021	Movement Decoding using Spatio-Spectral Features of Cortical and Subcortical Local Field Potential
10/04	Achint	Kline, Palmer 2021	Gaussian Information Bottleneck and the Non-Perturbative Renormalization Group
10/11	Seth		CCN practice talk
10/18	Na Young		Neurobio retreat practice talk
10/25	Marija
11/01	Pranjal	Cowley et al. 2020, Hennig et al. 2021	Slow Drift of Neural Activity as a Signature of Impulsivity in Macaque Visual and Prefrontal Cortex, Learning is shaped by abrupt changes in neural engagement
11/08	Postdoc candidate talk
11/15	Raphael	Ritz & Shenhav	Humans reconfigure target and distractor processing to address distinct task demands
11/22	Thanksgiving
11/29	Daniela	Liu et al. 2021	Deep Probability Estimation

(Virtual) Lab Meeting Presentation Schedule Summer 2021

Date	Presenter	Authors	Paper & Blurb
05/05	Anne	Avitan et al.	Spontaneous and evoked activity patterns diverge over development
05/12	Sara	Weihao Sheng et al.	A fast image processing toolbox for all-optical closed-loop control of neuronal activities
05/19	Na Young	Donti et al.	DC3: A learning method for optimization with hard constraints
05/26	Daniela	Ho et al.; Dhariwal & Nichol	Denoising Diffusion Probabilistic Models; Diffusion Models Beat GANs on Image Synthesis
06/02	Kevin	Paul Bürkner & Emmanuel Charpentier	Modeling Monotonic Effects of Ordinal Predictors in Bayesian Regression Models
06/09	Miles	Stephenson et al.	On the geometry of generalization and memorization in deep neural networks
06/16		BRAIN Meeting
06/23	Trevor	Timothy Dunn et al	Geometric deep learning enables 3D kinematic profiling across species and environments
06/29	Seth	Aki Vehtari et al.	Pareto-smoothed importance sampling
07/06	Pranjal	McInnes et al. ; Bahri et al. ; Ko et al.	UMAP, Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams, Progressive Uniform Manifold Approximation and Projection
07/13	Achint	Wu et al. ; Shi et al.	MVAE, MMVAE
07/20		ICML
07/27	Raphael	Tomov, Schulz, & Gershman 2021	Multi-task reinforcement learning in humans
08/03	Miles	Joint with all-hands bird meeting
08/10	Anne	A. Umakantha et al.	Bridging neuronal correlations and dimensionality reduction
08/17	Daniela	van den Oord, Li, & Vinyals 2019	Representation Learning with Contrastive Predictive Coding

(Virtual) Lab Meeting Presentation Schedule Spring 2021

Date	Presenter	Authors	Paper & Blurb
01/08	John	Dai and Wipf	Diagnosing and Enhancing VAE Models
01/15	Anne Draelos	M. Genkin, O. Hughes, T. A. Engel	Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories
01/20	Daniela	Multiple, (see links)	Very rough Qual practice talk. These are the 3 papers I chose for the exam: Neural Discrete Representation Learning Variational Inference with Normalizing Flows Auto-Encoding Sequential Monte Carlo
01/27	Seth	N. A. Roy, ... , J. W. Pillow	Extracting the dynamics of behavior in sensory decision-making experiments
02/03	Kevin	Quillien, T.	When do we think that X caused Y?
02/10	Miles	Locatello et al.	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
02/17		--Canceled--	CNAP Recruiting
02/24		--Canceled--	Cosyne Conference
03/03	Richard	E. Fox, E. Sudderth, M. Jordan, A. Willsky	Nonparametric Bayesian Learning of Switching Linear Dynamical Systems
03/10	Trevor	Walker et al.	Chronic wireless neural population recordings with common marmosets
03/17		--Canceled--	DIBS Symposium
03/24	Seth		Research talk
03/31	Pranjal		CNAP Third year practice talk
04/07	John	Khemakhem et al.	Variational Autoencoders and Nonlinear ICA: A Unifying Framework
04/14	Daniela		Another Practice Talk for my Qual Exam (this is final one, promise). Thanks to everyone who helped me perfect 2 previous versions of this!
04/21	Achint	Ali Hasan et al.	Learning latent stochastic differential equations with variational auto-encoders
04/28	Raphael	Lieder et al.	Rational metareasoning and the plasticity of cognitive control

(Virtual) Lab Meeting Presentation Schedule Fall 2020

Date	Presenter	Authors	Paper & Blurb
08/21	Seth	Graving & Couzin	VAE-SNE: a deep generative model for simultaneous dimensionality reduction and clustering
08/28	Trevor	Trautmann	Accurate Estimation of Neural Population Dynamics without Spike Sorting
09/04	Pranjal	Haesemeyer, Schier, Engert (2019)	Convergent Temperature Representations in Artificial and Biological Neural Networks
09/11	Vision Fest	John talks at 3pm	How vision solves the sensor alignment problem
09/18	Daniela	Huang, Makhzani, Cao, Grosse (2020)	Evaluating Lossy Compression Rates for Deep Generative Models (https://arxiv.org/abs/2008.06653)
09/25	Kevin	Dowling, Zhao, Park (2020)	Non-parametric generalized linear model
10/02	Nicole Moiseyev	Li, Amvrosiadis, Rochefort, Onken (2020)	CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of Neuronal Populations
10/09	Anne Draelos	Abhranil Das and Ila R. Fiete	Systematic errors in connectivity inferred from activity in strongly recurrent networks
10/16	--	Hangout session	--
10/23	--	Scott Linderman talk in B&B	--
10/30	Kelsey	PyData Practice Talk
11/06	Dominic	1. Lee, et al. (2017) 2. Lee, et al. (2020)	1. YASS: Yet Another Spike Sorter 2. YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina
11/13	Na Young	A brief Review of Info-related VAE models	Auto-Encoding Variational Bayes β-VAE: Learning Basic Visual Concepts With A Constrained Variational Framework InfoVAE: Balancing Learning and Inference in Variational Autoencoders ControlVAE: Controllable Variational Autoencoder
11/20	Everyone	Lab check in
11/27	--	Thanksgiving holiday	--
12/04	Everyone	NeurIPS preview/planning meeting
12/11	--	NeurIPS Conference	--

Lab Meeting Presentation Schedule Summer Quarantine 2020

Date	Presenter	Authors	Paper & Blurb
05/08	Sam Yin	Zhou, Gao, Paninski	Disentangled sticky hierarchical Dirichlet process hidden Markov model
05/15	Kevin O'Neill	Gerstenberg et al., 2020	A counterfactual simulation model of causal judgment
05/22	Anne Draelos		Research update
05/29	---	Lab check-in, 2 min updates	---
06/05	Seth Madlon-Kay	Coming soon	Coming soon
06/12	Daniel Sprague	Vincent Adam	Non-linear Regression Models For Behavioral and Neural Data Analysis
06/19		Juneteenth Holiday
06/26	Daniela De Albuquerque	Hidenori Tanaka	Pruning neural networks without any data by iteratively conserving synaptic flow
07/03		Fourth of July holiday
07/10	Pranjal Gupta	Williams et al, 2018	Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis
07/17	Everyone is busy	-- canceled --	NMA, ICML, ...
07/24	John Pearson		Improving Lab Equity
07/31	Anne Draelos	Bolus et. al.	State-space optimal feedback control of optogenetically driven neural activity
08/07	John Pearson	van den Oord et al.	Neural Discrete Representation Learning
08/14	Kelsey McDonald	Gershman & Cikara, 2020	Social-Structure Learning

Lab Meeting Presentation Schedule Spring 2020

Date	Presenter	Authors	Paper & Blurb
01/10	Kelsey McDonald	Smith et al., 2019	Widespread temporal coding of cognitive control in the human prefrontal cortex
01/17	Seth Madlon-Kay	Xiao-Li Meng, 2018	Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election
01/24	Rotating students		Presentations about previous research
01/31	Jack Goffinet	Sani, Pesaran, Shanechi (2019)	Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification
02/07	Anne Draelos	Papers on voltage imaging	VolPy: automated and scalable analysis pipelines for voltage imaging datasets and Bright and photostable chemigenetic indicators for extended in vivo voltage imaging
02/14	Na Young Jun		Student Seminar Practice Talk
02/21	Kevin O'Neill	Lennart Wittkuhn and Nicolas W. Schucklklja	Faster than thought: Detecting sub-second activation sequences with sequential fMRI pattern analysis
02/28	cancelled
03/06	Na Young Jun	Latimer et al.	Inferring synaptic inputs from spikes with a conductance-based neural encoding model
03/13	Sam Yin	Wolinski et al.; Wenzel et al.	Interpreting a Penalty as the Influence of a Bayesian Prior; How Good is the Bayes Posterior in Deep Neural Networks Really?
03/20	---	Canceled; virtual check-in	---
03/26	Seth Madlon-Kay	Loper, Blei, Cunningham, Paninski	General linear-time inference for Gaussian Processes on one dimension
04/03	Nicole Moiseyev	Minden, Pehlevan, and Chklovskii, 2018	Biologically Plausible Online Principal Component Analysis Without Recurrent Neural Dynamics
04/10	---	Virtual Check-in	---
04/17	Kelsey McDonald	Attention is All you Need
04/24	Jack Goffinet	Markovian score climbing: VI with KL(p,q)	Naesseth, Lindsten, Blei
05/01	Daniela de Albuquerque	Variational Autoencoders with Normalizing Flow Decoders	Morrow, Chiu

Lab Meeting Presentation Schedule Fall 2019

Date	Presenter	Authors	Paper & Blurb
08/22	Jack Goffinet	Sainburg et al.	Parallels in the sequential organization of birdsong and human speech
08/29	Pranjal Gupta	Maheswaranathan et al.	Universality and individuality in neural dynamics across large populations of recurrent networks
09/05	Sam Yin	Lee et al. & Zaheer et al.	Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks & Deep Sets
09/12	---	No lab meeting	---
09/19	Everyone	NIPS 2019 Papers	Wiki to add papers
09/26	---	Canceled	---
10/03	Rotation students
10/10	Kelsey McDonald	ECoG Data Presentation
10/17	Seth Madlon-Kay	Hanh et al. x2	Regularization and confounding in linear regression for treatment effect estimation & Bayesian regression tree models for causal inference: Regularization, confounding, and heterogeneous effects
10/24	Anne Draelos	practice talk
10/31	Kevin O'Neill	2nd Year Practice Talk
11/07	----	CCN Social Hour	---
11/14	Sam Yin	Variational Inference & Sequential Monte Carlo	Filtering Variational Objectives & Auto-Encoding Sequential Monte Carlo & Variational Sequential Monte Carlo
11/14	Jack Goffinet	Jankowiak, Pleiss, Gardner	Sparse Gaussian Process Regression Beyond Variational Inference
11/21	Chaichontat Sriworarat	Stuart et al.	Comprehensive Integration of Single-Cell Data
11/28	---	Thanksgiving holiday, no meeting	---
12/05	Pranjal Gupta	2nd year practice talk
12/12	Lan Luo		Rotation Projects. Lan: Seeking preference of prefrontal cortex neurons in strategic games

Lab Meeting Presentation Schedule Summer 2019

Date	Presenter	Authors	Paper & Blurb
05/23	Pranjal Gupta	Cunningham and Yu (2014); Kobak et al. (2016)	Dimensionality reduction for large-scale neural recordings; Demixed PCA
05/30	Wenxi Xiao		Thesis Work
06/06	Meredith Schmehl		Perception, Experience, and Behavior (research history and future work)
06/13	Kevin O'Neill		Research background & directions
06/20	Seth Madlon-Kay		Research background / practice talk
06/27	Rachael Wright		Research background & future work
07/04	---	Holiday!	---
07/11	Kelsey McDonald	Eric Schultz et al & Sam Gershman, 2019	Structured, uncertainty-driven exploration in real-world consumer choice
07/18	---	Canceled	---
07/25	Anne Draelos	A. Degleris, B. Antin, S. Ganguli, A. H. Williams	Fast Convolutive Nonnegative Matrix Factorization Through Coordinate and Block Coordinate Updates
08/01	Wenxi Xiao & Kevin O'Neill		Rotation Projects. Kevin: Modeling Neural Populations with SpikingNeuralNets.jl;
08/08	Rachael Wright & Meredith Schmehl		Rotation Projects. Meredith: Probing the Auditory Periphery with McGurk Stimuli
08/15	Na Young Jun	Atick & Redlich (1992)	What Does the Retina Know about Natural Scenes?

Lab Meeting Presentation Schedule Spring 2019

Date	Presenter	Authors	Paper & Blurb
01/04	Kelsey McDonald	Kane, Bornstein, Shenhav, Wilson, Daw, Cohen	Rats exhibit similar biases in foraging and intertemporal choice tasks
01/11	Jack Goffinet		Animal Vocalization Research Update
01/18	Sam Yin	Garnelo et al.	Neural Processes (Slides)
01/25	Anne Draelos	Lee et al.	A compressed sensing framework for efficient dissection of neural circuits
02/07	Kelsey McDonald		Practice talk for MAP
02/14	Nayoung Jun		Efficient Coding of the Retina Research Update
02/21	Jack Goffinet	Brunel & Nadal 1998	Mutual information, fisher information, and population coding
		Ganguli & Simoncelli 2010	Implicit encoding of prior probabilities in optimal neural populations
02/28	Kelsey McDonald		Practice talk for 3rd year talk
03/07	Sam Yin	Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt, David Duvenaud	Neural Ordinary Differential Equations
03/14	Anne Draelos	Gal Mishne, Adam S. Charles	Learning spatially-correlated temporal dictionaries for calcium imaging
03/21	Kelsey McDonald		Practice talk for Duke Machine Learning Day
03/28	Nayoung Jun		Superposition of many models into one
04/04	Anne Draelos, Sam Yin		Practice talk for Neurobio student seminar & theory journal club
04/11	Jack Goffinet	Knoblauch, Jewson, & Damoulas 2019	Generalized Variational Inference
04/18	Anne Draelos	Soltanian-Zadeh et. al. (Duke University)	Fast and robust active neuron segmentation in two photon calcium imaging using spatiotemporal deep learning
04/25	John Pearson		Lessons about academic success
05/02	Kelsey McDonald	Causal Inference About Good and Bad Outcomes (Sam Gershman)
05/09	Jack Goffinet		Research Update
05/16	---	CCN Retreat!	---