Publications

You can also find many DtAK publications on Finale's Google Scholar profile.

Failures of Variational Autoencoders and their Effects on Downstream Tasks
Yacoby Y, Pan W, Doshi-Velez F
BaCOUn - Bayesian Classifers with Out-of-Distribution Uncertainty
Guenais T, Vamvourellis D, Yacoby Y, Doshi-Velez F, Pan W
Learned Uncertainty-Aware (LUNA) Bases for Bayesian Regression using Multi-Headed Auxiliary Networks
Thakur S, Lorsung C, Yacoby Y, Doshi-Velez F, Pan W
Power-Constrained Bandit
Yao J, Brunskill E, Pan W, Murphy S, Doshi-Velez F
Characterizing and Avoiding Problematic Global Optima of Variational Autoencoders
Yacoby Y, Pan W, Doshi-Velez F
Defining Admissible Rewards for High-Confidence Policy Evaluation in Batch Reinforcement Learning
Prasad N, Engelhardt B, Doshi-Velez F
Prediction Focused Topic Models via Feature Selection
Ren J, Kunes R, Doshi-Velez F
POPCORN: Partially Observed Prediction Constrained Reinforcement Learning
Futoma J, Hughes M, Doshi-Velez F
Regional Tree Regularization for Interpretability in Deep Neural Networks
Wu M, Parbhoo S, Hughes M, Kindle R, Celi L, Zazzi M, Volker R, Doshi-Velez F
Regional Tree Regularization for Interpretability in Deep Neural Networks
Wu M, Parbhoo S, Hughes M, Kindle R, Celi L, Zazzi M, Volker R, Doshi-Velez F
Ensembles of Locally Independent Prediction Models
Ross A, Pan W, Celi L, Doshi-Velez F
Identifying Distinct, Effective Treatments for Acute Hypotension with SODA-RL: Safely Optimized Diverse Accurate Reinforcement Learning
Futoma F, Masgood M, Doshi-Velez F
Interpretable Batch IRL to extract clinician goals in ICU Hypotension Management
Srinivasan S, Doshi-Velez F
Big Data in the Assessment of Pediatric Medication Safety
McMahon A, Cooper W, Brown J, Carleton B, Doshi-Velez F, Kohane I, Goldman J, Hoffman M, Kamaleswaran R, Sakiyama M, et al.
Evaluating Machine Learning Articles
Doshi-Velez F, Perlis R
Predicting treatment dropout after antidepressant initiation
Pradier M, McCoy T, Hughes M, Perlis R, Doshi-Velez F
A Particle-Based Variational Approach to Bayesian Non-negative Matrix Factorization
Masood M, Doshi-Velez F
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Ghosh S, Yao J, Doshi-Velez F
Defining Admissible Rewards for High Confidence Policy Evaluation
Prasad N, Engelhardt B, Doshi-Velez F
Controlled Direct Effect Priors for Bayesian Neural Networks
Ross A, Du J, Sharvit Y, Doshi-Velez F
Integrating AI Recommendations into The Pharmacologic Management of Major Depressive Disorder
Jacobs M, Perlis R, Pradier M, Doshi-Velez F, Mynatt E, Gajos K
Prediction Focused Topic Models Via Vocab Filtering
Ren J, Russell R, Doshi-Velez F
Challenges in Computing and Optimizing Upper Bounds of Marginal Likelihood based on Chi-Square Divergences
Pradier M, Hughes M, Doshi-Velez F
Projected BNNs: Avoiding Weight-space Pathologies by Learning Latent Representations of Neural Network Weights
Pradier M, Pan W, Yao J, Ghosh S, Doshi-Velez F
Prediction Focused Topic Models for Electronic Health Records
Ren J, Kunes R, Doshi-Velez F
Do no harm: A roadmap for responsible machine learning for healthcare
Wiens J, Saria S, Sendak M, Ghassemi M, Liu V, Doshi-Velez F, Jung K, Heller K, Kale D, Saeed M, et al.
Summarizing Agent Strategies
Amir O, Doshi-Velez F, Sarne D
The Application of Machine Learning Methods to Evaluate Predictors for Live Birth in Programmed Thaw Cycles
Vaughan D, Pan W, Yacoby Y, Seidler E, Leung A, Doshi-Velez F, Sakkas D
Output-Constrained Bayesian Neural Network
Yang W, Lorch L, Graule M, Srinivasan S, Suresh A, Yao J, Pradier M, Doshi-Velez F
Output-Constrained Bayesian Neural Networks
Yang W, Lorch L, Graule M, Srinivasan S, Suresh A, Yao J, Pradier M, Doshi-Velez F
Mitigating Model Non-Identifiability in BNN with Latent Variables
Yacoby Y, Pan W, Doshi-Velez F
Quality of Uncertainty Quantification for Bayesian Neural Network Inference
Yao J, Pan W, Ghosh S, Doshi-Velez F
Poisson Process Bayesian Neural Networks
Coker B, Pradier M, Doshi-Velez F
Toward Robust Policy Summarization
Lage I, Lifschitz D, Doshi-Velez F, Amir O
Toward Robust Summarization of Agent Policies
Lage I, Lifschitz D, Doshi-Velez F, Amir O
Human Evaluation of Models Built for Interpretability
Lage I, Chen E, He J, Narayanan M, Kim B, Gershman S, Doshi-Velez F
Truly Batch Apprenticeship Learning with Deep Successor Features
Srinivasan S, Lee D, Doshi-Velez F
Exploring Computational User Models for Agent Policy Summarization
Lage I, Lifschitz D, Doshi-Velez F, Amir O
Explainable Reinforcement Learning via Reward Decomposition
Juozapaitis Z, Koul A, Fern A, Erwig M, Doshi-Velez F
Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies
Masood M, Doshi Velez F
Combining Parametric and Nonparametric Models for off-policy evaluation
Gottesman O, Liu Y, Susser E, Brunskill E, Doshi-Velez F
Assessing topic model relevance: Evaluation and informative priors
Fan A, Doshi-Velez F, Miratrix L
Guidelines for reinforcement learning in healthcare
Gottesman O, Johansson F, Komorowski M, Faisal A, Sontag D, Doshi-Velez F, Celi L
An Evaluation of the Human-Interpretability of Explanation
Lage I, Chen E, He J, Narayanan M, Gershman S, Kim B, Doshi-Velez F
Projected BNNs: Avoiding weight-space pathologies by projecting neural network weights
Pradier MF, Pan W, Yao J, Ghosh S, Doshi-Velez F
Hierarchical Stick-breaking Feature Paintbox
Fernandez-Pradier M, Pan W, Yao M, Singh R, Doshi-Velez F
Prediction-Constrained POMDPs
Futoma J, Hughes MC, Doshi-Velez F
Improving counterfactual reasoning with kernelised dynamic mixing models
Parbhoo S, Gottesman O, Ross AS, Komorowski M, Faisal A, Bon I, Roth V, Doshi-Velez F
Human-in-the-Loop Interpretability Prior
Lage I, Ross A, Kim B, Gershman S, Doshi-Velez F
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
Wu M, Hughes M, Parbhoo S, Zazzi M, Roth V, Doshi-Velez F
Diversity-Inducing Policy Gradient: Using MMD to find a set of policies that are diverse in terms of stete-visitation
Masood MA, Doshi-Velez F
Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning
Peng X, Ding Y, Wihl D, Gottesman O, Komorowski M, Lehman L-wei H, Ross A, Faisal A, Doshi-Velez F
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors
Ghosh S, Yao J, Doshi-Velez F
Decomposition of Uncertainty in Bayesian Deep Learning for Efficient and Risk-sensitive Learning
Depeweg S, Hernandez-Lobato JM, Doshi-Velez F, Udluft S
Weighted Tensor Decomposition for Learning Latent Variables with Partial Data
Gottesman O, Pan W, Doshi-Velez F
Semi-Supervised Prediction-Constrained Topic Models
Hughes MC, Hope G, Weiner L, Thomas H. McCoy J, Perlis RH, Sudderth E, Doshi-Velez F
Agent Strategy Summarization
Amir O, Doshi-Velez F, Sarne D
Accountability of AI Under the Law: The Role of Explanation
Doshi-Velez F, Kortz M, Budish R, Bavitz C, Gershman S, O'Brien D, Shieber S, Waldo J, Weinberger D, Wood A
Unsupervised Grammar Induction with Depth-bounded PCFG
Jin L, Doshi-Velez F, Miller T, Schuler W, Schwartz L
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
Ross AS, Doshi-Velez F
Direct Policy Transfer via Hidden Parameter Markov Decision Processes
Yao J, Killian T, Konidaris G, Doshi-Velez F
Behaviour Policy Estimation in Off-Policy Policy Evaluation: Calibration Matters
Raghu A, Gottesman O, Liu Y, Komorowski M, Faisal A, Doshi-Velez F, Brunskill E
Stitched Trajectories for Off-Policy Learning
Sussex S, Gottesman O, Liu Y, Murphy S, Brunskill E, Doshi-Velez F
Representation Balancing MDPs for Off-Policy Policy Evaluation
Liu Y, Gottesman O, Raghu A, Komorowski M, Faisal A, Doshi-Velez F, Brunskill E
Regularizing Tensor Decomposition Methods by Optimizing Pseudo-Data
Gottesman O, Doshi-Velez F
Learning Qualitatively Diverse and Interpretable Rules for Classification
Ross AS, Pan W, Doshi-Velez F
Depth-bounding is effective: Improvements and Evaluation of Unsupervised PCFG Induction
Jin L, Doshi-Velez F, Miller T, Schuler W, Schwartz L
Considerations for Evaluation and Generalization in Interpretable Machine Learning
Doshi-Velez F, Kim BEscalante H, Escalera S, Guyon I, Baró X, Güçlütürk Y, Güçlü U, van Gerven MAJ
PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models
Glueck M, Naeini MP, Doshi-Velez F, Chevalier F, Khan A, Wigdor D, Brudno M
Predicting intervention onset in the ICU with switching state space models
Ghassemi M, Wu M, Hughes MC, Szolovits P, Doshi-Velez F
PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models
Glueck M, Naeini MP, Doshi-Velez F, Chevalier F, Khan A, Wigdor D, Brudno M
The Neural LASSO: Local Linear Sparsity for Interpretable Explanations
Ross AS, Lage I, Doshi-Velez F
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
Wu M, Hughes M, Parbhoo S, Zazzi M, Roth V, Doshi-Velez F
Counterfactual Reasoning with Dynamic Switching Models for HIV Therapy Selection
Parbhoo S, Roth V, Doshi-Velez F
Prediction-Constrained Topic Models for Antidepressant Recommendation
Hughes MC, Hope G, Weiner L, McCoy TH, Perlis RH, Sudderth EB, Doshi-Velez F
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Ghosh S, Doshi-Velez F
Structured Variational Autoencoders for the Beta-Bernoulli Process
Singh R, Ling J, Doshi-Velez F
Clustering LaTeX Solutions to Machine Learning Assignments for Rapid Assessment
Tan S, Doshi-Velez F, Quiroz J, Glassman E
Uncertainty Decomposition in Bayesian Neural Networks with Latent Variables
Depeweg S, Hernandez-Lobato JM, Doshi-Velez F, Udluft S
Combining Kernel and Model Based Learning for HIV Therapy Selection
Parbhoo S, Bogojeska J, Zazzi M, Roth V, Doshi-Velez F
Prior Matters: Simple and General Methods for Evaluating and Improving Topic Quality in Topic Modeling
Fan A, Doshi-Velez F, Miratrix L
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
Killian T, Daulton S, Konidaris G, Doshi-Velez F
A Bayesian Framework for Learning Rule Sets for Interpretable Classification
Wang T, Rudin C, Doshi-Velez F, Liu Y, Klampfl E, MacNeille P
Right for the Right Reasons: Training Differentiable Models by Constraining their Explananations
Ross AS, Hughes MC, Doshi-Velez F
Restricted Indian Buffet Processes
Doshi-Velez F, Williamson S
Understanding Vasopressor Intervention and Weaning: Risk Prediction in a Public Heterogeneous Clinical Time Series Database
Wu M, Ghassemi M, Fend M, Celi LA, Szolovits P, Doshi-Velez F
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks
Depewag S, Hernández-Lobato JM, Doshi-Velez F, Udluft S
Combining Kernel and Model Based Learning for HIV Therapy Selection
Parbhoo S, Bogojeska J, Zazzi M, Roth V, Doshi-Velez F
Transfer Learning Across Patient Variations with Hidden Parameter Markov Decision Processes
Killian TW, Konidaris G, Doshi-Velez F
Supervised topic models for clinical interpretability
Hughes MC, Elibol HM, McCoy T, Perlis R, Doshi-Velez F
Robust Posterior Exploration in NMF
Masood MA, Doshi-Velez F
Memory-Bounded Left-Corner Unsupervised Grammar Induction on Child-Directed Input
Shain C, Bryce W, Jin L, Krakovna V, Doshi-Velez F, Miller T, Schuler W, Schwartz L
Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizations
Doshi-Velez F, Konidaris G
Cross-Corpora Unsupervised Learning of Trajectories in Autism Spectrum Disorders
Elibol M, Nguyen V, Linderman S, Johnson M, Hashmi A, Doshi-Velez F
Spectral M-estimation with Application to Hidden Markov Models: Supplementary Material
Tran D, Kim M, Doshi-Velz F
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations
Pan W, Doshi-Velez F
Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice
Xia X, Protopapas P, Doshi-Velez F
An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization
Masood A, Pan W, Doshi-Velez F
Machine Learning Approaches to Environmental Disturbance Rejection in Multi-Axis Optoelectronic Force Sensors
Gafford J, Doshi-Velez F, Wood R, Walsh C
Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder
Lingren T, Chen P, Bochenek J, Doshi-Velez F, Manning-Courtney P, Bickel J, Welchons LW, Reinhold J, Bing N, Ni Y, et al.
Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models
Krakovna V, Doshi-Velez F
Bayesian Or's of And's for Interpretable Classification with Application to Context Aware Recommender Systems
Wang T, Rudin C, Doshi-Velez F, Liu Y, Klampfl E, MacNeille P
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
Kim B, Shah JA, Doshi-Velez F
Prevalence of Inflammatory Bowel Disease Among Patients with Autism Spectrum Disorders
Doshi-Velez F, Avillach P, Palmer N, Bousvaros A, Ge Y, Fox K, Steinberg G, Spettell C, Juster I, Kohane I
Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning
Doshi-Velez F, Pfau D, Wood F, Roy N
HackEbola with Data: On the hackathon format for timely data analysis.
Doshi-Velez F, Marshall YE
Graph-Sparse LDA: A Topic Model with Structured Sparsity
Doshi-Velez F, Wallace BC, Adams RP
Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis
Doshi-Velez F, Ge Y, Kohane I
Graph-Sparse LDA: A Topic Model with Structured Sparsity
Doshi-Velez F, Wallace B, Adams R
Hidden Parameter Markov Decision Processes: An Emerging Paradigm for Modeling Families of Related Tasks
Konidaris G, Doshi-Velez F
Unfolding Physiological State: Mortality Modelling in Intensive Care Units
Ghassemi M, Naumann T, Doshi-Velez F, Brimmer N, Joshi R, Rumshisky A, Szolovits P