reproducibilityindex.ai

Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].

Transactions on Machine Learning Research (TMLR) - 2022

Website:

Venue	Year	Papers	Reproducibility Score Reproducibility Score based on Gundersen et al. (2025)	Documentation Score Global mean is the average score over the seven reproducibility variables for empirical research papers.	% Empirical Percentage of papers that are empirical research vs theoretical research	% Industry Percentage of empirical research papers with at least one author from Industry	Website
TMLR	2022	216	0.61	4.23	96.3%	48.08%

Search Papers

	Pseudocode	Open Source Code	Open Datasets	Dataset Splits	Hardware Specification	Software Dependencies	Experiment Setup
A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey	❌	❌	✅	✅	✅	✅	✅	5
A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful	❌	✅	❌	✅	❌	❌	✅	3
A Generalist Agent	❌	❌	✅	✅	✅	❌	✅	4
A Note on "Assessing Generalization of SGD via Disagreement"	❌	✅	✅	✅	❌	❌	✅	4
A Rigorous Study Of The Deep Taylor Decomposition	✅	✅	✅	❌	❌	❌	❌	3
A Self-Supervised Framework for Function Learning and Extrapolation	❌	❌	❌	✅	❌	❌	✅	2
A Simple Convergence Proof of Adam and Adagrad	❌	❌	✅	❌	✅	❌	✅	3
A Snapshot of the Frontiers of Client Selection in Federated Learning	❌	❌	✅	❌	❌	❌	❌	1
A Stochastic Optimization Framework for Fair Risk Minimization	✅	✅	✅	✅	❌	❌	✅	5
A Unified Domain Adaptation Framework with Distinctive Divergence Analysis	❌	❌	✅	✅	✅	❌	✅	4
A Unified Survey on Anomaly, Novelty, Open-Set, and Out of-Distribution Detection: Solutions and Future Challenges	✅	✅	✅	✅	❌	❌	❌	4
A geometrical connection between sparse and low-rank matrices and its application to manifold learning	❌	❌	✅	✅	❌	❌	✅	3
ANCER: Anisotropic Certification via Sample-wise Volume Maximization	✅	✅	✅	✅	✅	❌	✅	6
Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance	✅	✅	✅	❌	✅	❌	✅	5
Adversarial Feature Augmentation and Normalization for Visual Recognition	✅	✅	✅	✅	✅	❌	✅	6
Algorithms and Theory for Supervised Gradual Domain Adaptation	❌	❌	✅	❌	❌	❌	❌	1
An Efficient One-Class SVM for Novelty Detection in IoT	✅	✅	✅	✅	✅	✅	✅	7
An approximate sampler for energy-based models with divergence diagnostics	✅	❌	✅	❌	❌	❌	✅	3
An empirical study of implicit regularization in deep offline RL	✅	❌	✅	✅	❌	❌	✅	4
Approximate Policy Iteration with Bisimulation Metrics	✅	❌	❌	❌	✅	❌	✅	3
Approximating 1-Wasserstein Distance with Trees	✅	✅	✅	✅	✅	❌	✅	6
Attentive Walk-Aggregating Graph Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Attribute Prediction as Multiple Instance Learning	❌	❌	✅	✅	❌	❌	✅	3
Auto-Lambda: Disentangling Dynamic Task Relationships	❌	✅	✅	❌	❌	❌	✅	3
Bayesian Methods for Constraint Inference in Reinforcement Learning	✅	❌	✅	❌	❌	❌	✅	3
Behind the Machine’s Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention	❌	❌	✅	❌	❌	❌	✅	2
Benchmarking Progress to Infant-Level Physical Reasoning in AI	❌	✅	✅	✅	❌	❌	❌	3
Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress	❌	✅	✅	✅	✅	❌	✅	5
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation	✅	✅	✅	❌	❌	❌	❌	3
Boosting Search Engines with Interactive Agents	✅	✅	✅	✅	✅	❌	✅	6
Bridging Offline and Online Experimentation: Constraint Active Search for Deployed Performance Optimization	✅	❌	✅	✅	✅	❌	✅	5
COIN++: Neural Compression Across Modalities	❌	✅	✅	✅	✅	✅	✅	6
Calibrated Selective Classification	✅	✅	✅	✅	❌	❌	✅	5
Can You Win Everything with A Lottery Ticket?	❌	✅	✅	✅	❌	❌	✅	4
Causal Feature Selection via Orthogonal Search	✅	✅	✅	✅	❌	❌	✅	5
Centroids Matching: an efficient Continual Learning approach operating in the embedding space	❌	✅	✅	❌	❌	❌	✅	3
Clustering units in neural networks: upstream vs downstream information	✅	✅	✅	❌	❌	❌	✅	4
CoCa: Contrastive Captioners are Image-Text Foundation Models	❌	❌	✅	✅	✅	❌	✅	4
Collaborative Algorithms for Online Personalized Mean Estimation	✅	✅	✅	❌	❌	❌	✅	4
Competition over data: how does data purchase affect users?	✅	✅	✅	✅	❌	❌	✅	5
Completeness and Coherence Learning for Fast Arbitrary Style Transfer	❌	❌	✅	❌	✅	❌	✅	3
Complex-Valued Autoencoders for Object Discovery	❌	✅	✅	✅	✅	✅	✅	6
Concave Utility Reinforcement Learning with Zero-Constraint Violations	✅	❌	❌	❌	✅	❌	✅	3
Conformal Prediction Intervals with Temporal Dependence	✅	✅	✅	✅	❌	❌	✅	5
Controllable Generative Modeling via Causal Reasoning	✅	❌	✅	❌	❌	❌	✅	3
Convergence of denoising diffusion models under the manifold hypothesis	❌	❌	❌	❌	❌	❌	❌	0
Counterfactual Learning with Multioutput Deep Kernels	❌	✅	✅	✅	✅	❌	✅	5
DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture	✅	❌	✅	❌	✅	✅	❌	4
DR-DSGD: A Distributionally Robust Decentralized Learning Algorithm over Graphs	✅	❌	✅	✅	❌	❌	✅	4
Data Leakage in Federated Averaging	✅	✅	✅	✅	✅	❌	✅	6
Decoder Denoising Pretraining for Semantic Segmentation	❌	❌	✅	✅	✅	❌	✅	4
Decoding EEG With Spiking Neural Networks on Neuromorphic Hardware	❌	✅	✅	✅	✅	❌	✅	5
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter	❌	✅	✅	✅	✅	❌	✅	5
Deep Classifiers with Label Noise Modeling and Distance Awareness	✅	✅	✅	✅	✅	❌	✅	6
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure	✅	✅	✅	❌	✅	❌	✅	5
Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach	✅	✅	✅	✅	✅	✅	✅	7
Deformation Robust Roto-Scale-Translation Equivariant CNNs	❌	✅	✅	✅	❌	❌	✅	4
Degradation Attacks on Certifiably Robust Neural Networks	✅	✅	✅	✅	✅	❌	✅	6
Diagnosing and Fixing Manifold Overfitting in Deep Generative Models	❌	✅	✅	❌	❌	❌	✅	3
Did I do that? Blame as a means to identify controlled effects in reinforcement learning	❌	❌	✅	✅	❌	❌	✅	3
Differentiable Model Compression via Pseudo Quantization Noise	❌	✅	✅	✅	✅	❌	✅	5
Differentially Private Stochastic Expectation Propagation	✅	✅	✅	✅	❌	❌	✅	5
DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents	✅	✅	✅	✅	✅	❌	✅	6
Diffusion Models for Video Prediction and Infilling	✅	✅	✅	✅	✅	❌	✅	6
Direct Molecular Conformation Generation	❌	✅	✅	✅	✅	❌	✅	5
Distributed Stochastic Algorithms for High-rate Streaming Principal Component Analysis	✅	❌	✅	❌	❌	❌	✅	3
Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks	❌	✅	✅	✅	❌	❌	✅	4
Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?	❌	❌	❌	❌	❌	❌	❌	0
Do better ImageNet classifiers assess perceptual similarity better?	✅	✅	✅	✅	❌	❌	✅	5
Does Entity Abstraction Help Generative Transformers Reason?	❌	❌	✅	✅	✅	✅	✅	5
Domain Invariant Adversarial Learning	✅	✅	✅	✅	❌	❌	✅	5
Domain-invariant Feature Exploration for Domain Generalization	❌	✅	✅	✅	❌	❌	✅	4
Efficient CDF Approximations for Normalizing Flows	✅	✅	✅	❌	✅	❌	✅	5
Efficient Gradient Flows in Sliced-Wasserstein Space	✅	❌	✅	✅	✅	❌	✅	5
Emergent Abilities of Large Language Models	❌	❌	✅	❌	❌	❌	❌	1
Enhanced gradient-based MCMC in discrete spaces	✅	❌	✅	❌	❌	✅	✅	4
Ensembles of Classifiers: a Bias-Variance Perspective	✅	❌	✅	✅	❌	❌	✅	4
Equivariant Mesh Attention Networks	✅	✅	✅	✅	❌	❌	✅	5
Estimating Potential Outcome Distributions with Collaborating Causal Networks	❌	✅	✅	✅	✅	❌	✅	5
Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning	✅	✅	✅	✅	✅	❌	✅	6
Explicit Group Sparse Projection with Applications to Deep Learning and NMF	✅	✅	✅	❌	❌	❌	✅	4
Exploring Efficient Few-shot Adaptation for Vision Transformers	❌	✅	✅	✅	❌	❌	✅	4
Exploring Generative Neural Temporal Point Process	✅	✅	✅	✅	✅	❌	✅	6
Exploring the Learning Mechanisms of Neural Division Modules	❌	✅	✅	✅	✅	❌	✅	5
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images	✅	✅	✅	✅	❌	❌	✅	5
Extracting Local Reasoning Chains of Deep Neural Networks	❌	❌	✅	✅	✅	❌	✅	4
FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data	✅	✅	✅	✅	❌	❌	✅	5
Fail-Safe Adversarial Generative Imitation Learning	❌	✅	✅	✅	❌	❌	❌	3
Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed	❌	✅	✅	✅	❌	❌	✅	4
Faking Interpolation Until You Make It	✅	✅	✅	✅	✅	❌	✅	6
Fast and Accurate Spreading Process Temporal Scale Estimation	✅	❌	✅	❌	❌	❌	✅	3
FedShuffle: Recipes for Better Use of Local Work in Federated Learning	✅	❌	✅	✅	❌	✅	✅	5
Finding and Fixing Spurious Patterns with Explanations	✅	✅	✅	✅	❌	❌	✅	5
Fingerprints of Super Resolution Networks	❌	❌	✅	✅	❌	❌	✅	3
Flipped Classroom: Effective Teaching for Time Series Forecasting	❌	✅	✅	✅	❌	❌	✅	4
Fourier Sensitivity and Regularization of Computer Vision Models	✅	❌	✅	✅	❌	❌	✅	4
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality	✅	❌	✅	❌	❌	❌	✅	3
GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation	✅	✅	✅	✅	✅	❌	✅	6
GIT: A Generative Image-to-text Transformer for Vision and Language	❌	❌	✅	✅	❌	❌	✅	3
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets	❌	✅	✅	✅	✅	❌	✅	5
Generative Adversarial Neural Operators	✅	✅	✅	❌	❌	❌	✅	4
GhostSR: Learning Ghost Features for Efficient Image Super-Resolution	❌	❌	✅	✅	✅	❌	✅	4
Greedy Bayesian Posterior Approximation with Deep Ensembles	✅	✅	✅	✅	✅	❌	✅	6
HEAT: Hyperedge Attention Networks	✅	✅	✅	❌	❌	❌	✅	4
High Fidelity Visualization of What Your Self-Supervised Representation Knows About	❌	✅	✅	✅	❌	❌	❌	3
How Expressive are Transformers in Spectral Domain for Graphs?	❌	❌	✅	✅	✅	❌	✅	4
How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers	❌	✅	✅	✅	✅	❌	✅	5
INR-V: A Continuous Representation Space for Video-based Generative Tasks	❌	✅	✅	✅	✅	❌	✅	5
Identifiable Deep Generative Models via Sparse Decoding	✅	✅	✅	✅	✅	❌	✅	6
Identifying Causal Structure in Dynamical Systems	✅	✅	❌	❌	❌	❌	✅	3
If your data distribution shifts, use self-learning	❌	✅	✅	✅	✅	✅	✅	6
Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization	❌	✅	✅	✅	❌	❌	✅	4
Incorporating Sum Constraints into Multitask Gaussian Processes	✅	✅	✅	✅	✅	❌	✅	6
Indiscriminate Data Poisoning Attacks on Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions	❌	❌	❌	❌	❌	❌	❌	0
Integrating Rankings into Quantized Scores in Peer Review	✅	✅	✅	❌	❌	❌	✅	4
Interpretable Node Representation with Attribute Decoding	✅	❌	✅	✅	❌	❌	✅	4
Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation	✅	✅	✅	❌	❌	❌	✅	4
LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling	✅	❌	✅	❌	✅	❌	✅	4
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty	❌	❌	✅	✅	❌	❌	✅	3
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent	✅	✅	✅	✅	❌	✅	✅	6
Learning Algorithms for Markovian Bandits:\\Is Posterior Sampling more Scalable than Optimism?	✅	✅	✅	❌	❌	❌	✅	4
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning	❌	❌	✅	✅	❌	❌	✅	3
Learning the Transformer Kernel	❌	✅	✅	✅	✅	❌	✅	5
Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processes	✅	❌	✅	❌	❌	❌	✅	3
Linear algebra with transformers	❌	✅	❌	✅	✅	❌	✅	4
Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression	✅	❌	✅	✅	❌	❌	✅	4
Lookback for Learning to Branch	❌	❌	✅	✅	✅	✅	✅	5
MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth	✅	✅	✅	✅	✅	❌	✅	6
Mace: A flexible framework for membership privacy estimation in generative models	✅	❌	✅	✅	❌	❌	✅	4
Max-Affine Spline Insights Into Deep Network Pruning	✅	✅	✅	✅	✅	❌	✅	6
Mean-Field Langevin Dynamics : Exponential Convergence and Annealing	❌	✅	❌	❌	❌	❌	✅	2
Meta-Learning Sparse Compression Networks	❌	❌	✅	❌	❌	❌	✅	2
Mitigating Catastrophic Forgetting in Spiking Neural Networks through Threshold Modulation	✅	✅	✅	✅	❌	❌	✅	5
MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks	❌	❌	✅	✅	✅	❌	✅	4
Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning	❌	❌	❌	❌	❌	❌	✅	1
Modeling Object Dissimilarity for Deep Saliency Prediction	❌	✅	✅	✅	✅	❌	✅	5
Momentum Capsule Networks	✅	✅	✅	❌	❌	❌	✅	4
Multi-Agent Off-Policy TDC with Near-Optimal Sample and Communication Complexities	✅	❌	❌	❌	❌	❌	✅	2
Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias	❌	❌	✅	❌	❌	❌	❌	1
Multitask Online Mirror Descent	✅	❌	✅	❌	❌	❌	✅	3
NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes	❌	❌	✅	✅	✅	❌	✅	4
No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL	✅	❌	❌	❌	❌	❌	✅	2
NoiLin: Improving adversarial training and correcting stereotype of noisy labels	✅	✅	✅	✅	✅	❌	✅	6
Non-Deterministic Behavior of Thompson Sampling with Linear Payoffs and How to Avoid It	✅	✅	✅	✅	❌	❌	❌	4
Nonparametric Learning of Two-Layer ReLU Residual Units	✅	✅	✅	✅	✅	✅	✅	7
Nonstationary Reinforcement Learning with Linear Function Approximation	✅	❌	❌	❌	✅	❌	✅	3
Object-aware Cropping for Self-Supervised Learning	❌	❌	✅	✅	❌	❌	✅	3
On Characterizing the Trade-off in Invariant Representation Learning	❌	✅	✅	✅	❌	❌	✅	4
On Noise Abduction for Answering Counterfactual Queries: A Practical Outlook	❌	✅	✅	❌	✅	❌	✅	4
On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning	✅	❌	✅	✅	❌	❌	✅	4
On Robustness to Missing Video for Audiovisual Speech Recognition	❌	✅	✅	✅	❌	❌	✅	4
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces	✅	❌	❌	❌	❌	❌	❌	1
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning	❌	✅	✅	❌	❌	❌	✅	3
On the Adversarial Robustness of Vision Transformers	❌	✅	✅	✅	❌	❌	✅	4
On the Choice of Interpolation Scheme for Neural CDEs	❌	✅	✅	✅	✅	❌	✅	5
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons	✅	❌	✅	❌	❌	❌	✅	3
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning	✅	✅	❌	❌	❌	❌	✅	3
On the Origins of the Block Structure Phenomenon in Neural Network Representations	❌	❌	✅	✅	❌	❌	✅	3
On the Paradox of Certified Training	❌	❌	✅	✅	✅	❌	✅	4
On the link between conscious function and general intelligence in humans and machines	❌	❌	❌	❌	❌	❌	❌	0
Online Coresets for Parameteric and Non-Parametric Bregman Clustering	✅	❌	✅	❌	❌	❌	✅	3
Online Double Oracle	✅	✅	✅	❌	❌	❌	✅	4
Optimal Client Sampling for Federated Learning	✅	✅	✅	❌	❌	❌	✅	4
Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks	✅	❌	✅	✅	✅	❌	✅	5
Optimizing Intermediate Representations of Generative Models for Phase Retrieval	❌	❌	✅	✅	✅	❌	✅	4
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks	❌	❌	✅	✅	❌	❌	✅	3
Probabilistic Autoencoder	❌	✅	✅	✅	❌	❌	✅	4
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning	❌	✅	✅	❌	✅	❌	✅	4
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning	✅	✅	✅	✅	❌	❌	✅	5
Ranking Recovery under Privacy Considerations	❌	❌	❌	❌	❌	❌	✅	1
Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning	✅	✅	✅	✅	✅	❌	✅	6
Recurrent networks, hidden states and beliefs in partially observable environments	✅	❌	✅	❌	❌	❌	✅	3
Reinventing Policy Iteration under Time Inconsistency	✅	❌	❌	❌	❌	❌	✅	2
Representation Alignment in Neural Networks	❌	✅	✅	✅	✅	❌	✅	5
Robust and Data-efficient Q-learning by Composite Value-estimation	✅	✅	✅	❌	❌	❌	✅	4
SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning	✅	✅	✅	✅	❌	❌	✅	5
Scaling Autoregressive Models for Content-Rich Text-to-Image Generation	❌	❌	✅	✅	✅	❌	✅	4
Secure Domain Adaptation with Multiple Sources	✅	✅	✅	❌	✅	❌	✅	5
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection	✅	❌	✅	✅	✅	❌	✅	5
SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning	✅	❌	✅	✅	✅	❌	✅	5
Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores	✅	✅	✅	✅	✅	❌	✅	6
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation	❌	✅	✅	✅	❌	❌	❌	3
Sparse Coding with Multi-layer Decoders using Variance Regularization	✅	✅	✅	✅	✅	❌	✅	6
Sparse MoEs meet Efficient Ensembles	❌	✅	✅	✅	❌	❌	✅	4
Stable and Interpretable Unrolled Dictionary Learning	✅	✅	✅	✅	✅	✅	✅	7
Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation	✅	❌	✅	✅	❌	❌	✅	4
Structural Learning in Artificial Neural Networks: A Neural Operator Perspective	❌	❌	❌	❌	❌	❌	❌	0
Structured Uncertainty in the Observation Space of Variational Autoencoders	❌	✅	✅	❌	✅	❌	✅	4
Symbolic Regression is NP-hard	❌	❌	❌	❌	❌	❌	❌	0
Systematically and efficiently improving $k$-means initialization by pairwise-nearest-neighbor smoothing	✅	✅	✅	❌	✅	✅	✅	6
TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference	✅	❌	✅	✅	✅	❌	✅	5
TLDR: Twin Learning for Dimensionality Reduction	✅	✅	✅	✅	✅	❌	✅	6
Teacher’s pet: understanding and mitigating biases in distillation	❌	❌	✅	✅	❌	❌	✅	3
Teaching Models to Express Their Uncertainty in Words	❌	❌	❌	✅	❌	❌	✅	2
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning	❌	❌	✅	✅	❌	✅	✅	4
The Fundamental Limits of Neural Networks for Interval Certified Robustness	❌	❌	❌	❌	❌	❌	❌	0
The Graph Cut Kernel for Ranked Data	✅	✅	✅	✅	✅	❌	✅	6
Time Series Alignment with Global Invariances	✅	❌	✅	✅	❌	❌	✅	4
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning	✅	✅	✅	✅	❌	❌	✅	5
Uncertainty-Based Active Learning for Reading Comprehension	✅	❌	✅	✅	❌	❌	✅	4
Understanding AdamW through Proximal Methods and Scale-Freeness	✅	❌	✅	❌	❌	❌	✅	3
Understanding Linearity of Cross-Lingual Word Embedding Mappings	✅	✅	✅	❌	❌	❌	✅	4
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities	❌	✅	✅	✅	❌	✅	✅	5
Unimodal Likelihood Models for Ordinal Data	❌	✅	✅	✅	❌	❌	✅	4
Unsupervised Dense Information Retrieval with Contrastive Learning	❌	✅	✅	✅	❌	❌	✅	4
Unsupervised Learning of Neurosymbolic Encoders	✅	✅	✅	✅	✅	❌	✅	6
Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization	✅	❌	✅	✅	❌	❌	✅	4
Unsupervised Network Embedding Beyond Homophily	✅	✅	✅	❌	❌	❌	❌	3
Using unsupervised learning to detect broken symmetries, with relevance to searches for parity violation in nature.	❌	✅	✅	❌	❌	❌	✅	3
Variational Disentanglement for Domain Generalization	✅	❌	✅	✅	✅	✅	✅	6
Weight Expansion: A New Perspective on Dropout and Generalization	✅	❌	✅	✅	❌	❌	✅	4
Your Policy Regularizer is Secretly an Adversary	❌	❌	❌	❌	❌	❌	✅	1
ZerO Initialization: Initializing Neural Networks with only Zeros and Ones	✅	✅	✅	✅	❌	❌	✅	5
Zero-Shot Learning with Common Sense Knowledge Graphs	✅	✅	✅	✅	✅	❌	✅	6
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification	✅	✅	✅	✅	✅	❌	✅	6