Russ Salakhutdinov

Russ Salakhutdinov's AcademicInfluence.com Rankings

Russ Salakhutdinov

Computer Science

#375

World Rank

#390

Historical Rank

Algorithms

#24

World Rank

#24

Historical Rank

Machine Learning

#31

World Rank

#31

Historical Rank

Artificial Intelligence

#65

World Rank

#68

Historical Rank

computer-science Degrees

Download Badge

Computer Science

Why Is Russ Salakhutdinov Influential?

(Suggest an Edit or Addition)

According to Wikipedia, Ruslan "Russ" Salakhutdinov is a Canadian researcher of Tatar origin working in the field of artificial intelligence. He specializes in deep learning, probabilistic graphical models, and large-scale optimization.

(See a Problem?)

Russ Salakhutdinov's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Dropout: a simple way to prevent neural networks from overfitting (2014) (32886)
Reducing the Dimensionality of Data with Neural Networks (2006) (16584)
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (2015) (8487)
Improving neural networks by preventing co-adaptation of feature detectors (2012) (6887)
XLNet: Generalized Autoregressive Pretraining for Language Understanding (2019) (5668)
Probabilistic Matrix Factorization (2007) (4120)
Human-level concept learning through probabilistic program induction (2015) (2445)
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context (2019) (2399)
Unsupervised Learning of Video Representations using LSTMs (2015) (2249)
Deep Boltzmann Machines (2009) (2194)
Skip-Thought Vectors (2015) (2100)
Restricted Boltzmann machines for collaborative filtering (2007) (1967)
Neighbourhood Components Analysis (2004) (1821)
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books (2015) (1817)
Multimodal learning with deep Boltzmann machines (2012) (1607)
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo (2008) (1488)
Deep Sets (2017) (1434)
Semantic hashing (2009) (1335)
Revisiting Semi-Supervised Learning with Graph Embeddings (2016) (1315)
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models (2014) (1186)
Importance Weighted Autoencoders (2015) (1060)
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering (2018) (1002)
Evaluation methods for topic models (2009) (878)
Toward Controlled Generation of Text (2017) (832)
One shot learning of simple visual concepts (2011) (712)
On Exact Computation with an Infinitely Wide Neural Net (2019) (643)
Action Recognition using Visual Attention (2015) (635)
Multimodal Neural Language Models (2014) (626)
Deep Kernel Learning (2015) (620)
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units (2021) (588)
Replicated Softmax: an Undirected Topic Model (2009) (539)
Hamming Distance Metric Learning (2012) (520)
Deep learning for neuroimaging: a validation study (2013) (516)
Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure (2007) (515)
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning (2015) (510)
Multimodal Transformer for Unaligned Multimodal Language Sequences (2019) (490)
On the quantitative analysis of deep belief networks (2008) (488)
An Efficient Learning Procedure for Deep Boltzmann Machines (2012) (434)
Good Semi-supervised Learning That Requires a Bad GAN (2017) (411)
Gated-Attention Readers for Text Comprehension (2016) (389)
Efficient Learning of Deep Boltzmann Machines (2010) (384)
Predicting Deep Zero-Shot Convolutional Neural Networks Using Textual Descriptions (2015) (378)
Learning Deep Generative Models (2009) (357)
Improved Variational Autoencoders for Text Modeling using Dilated Convolutions (2017) (344)
Learning to share visual appearance for multiclass object detection (2011) (339)
Generating Images from Captions with Attention (2015) (336)
Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks (2016) (319)
Style Transfer Through Back-Translation (2018) (316)
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model (2017) (308)
The More You Know: Using Knowledge Graphs for Image Classification (2016) (286)
Spatially Adaptive Computation Time for Residual Networks (2016) (284)
Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text (2018) (277)
Modelling Relational Data using Bayesian Clustered Tensor Factorization (2009) (271)
Learning to Explore using Active Neural SLAM (2020) (259)
Multi-task Neural Networks for QSAR Predictions (2014) (256)
Review Networks for Caption Generation (2016) (238)
Think Locally, Act Globally: Federated Learning with Local and Global Representations (2020) (238)
Path-SGD: Path-Normalized Optimization in Deep Neural Networks (2015) (236)
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm (2010) (235)
Gated-Attention Architectures for Task-Oriented Language Grounding (2017) (230)
Multiple Futures Prediction (2019) (230)
Object Goal Navigation using Goal-Oriented Semantic Exploration (2020) (225)
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes (2007) (225)
Learning with Hierarchical-Deep Models (2013) (219)
One-shot learning by inverting a compositional causal process (2013) (218)
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) (218)
Neural Map: Structured Memory for Deep Reinforcement Learning (2017) (217)
Multi-Task Cross-Lingual Sequence Tagging from Scratch (2016) (213)
Learning Factorized Multimodal Representations (2018) (212)
Discriminative Transfer Learning with Tree-based Priors (2013) (212)
On the Quantitative Analysis of Decoder-Based Generative Models (2016) (210)
Stochastic Variational Deep Kernel Learning (2016) (206)
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification (2015) (190)
Learning Representations for Multimodal Data with Deep Belief Nets (2012) (187)
Optimization with EM and Expectation-Conjugate-Gradient (2003) (176)
Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels (2019) (172)
Robust Boltzmann Machines for recognition and denoising (2012) (170)
One-Shot Learning with a Hierarchical Nonparametric Bayesian Model (2011) (166)
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning (2019) (159)
Neural Topological SLAM for Visual Navigation (2020) (159)
Practical Large-Scale Optimization for Max-norm Regularization (2010) (159)
A Closer Look at Accuracy vs. Robustness (2020) (157)
Efficient Exploration via State Marginal Matching (2019) (152)
segDeepM: Exploiting segmentation and context in deep neural networks for object detection (2015) (147)
Architectural Complexity Measures of Recurrent Neural Networks (2016) (146)
Transfer Learning by Borrowing Examples for Multiclass Object Detection (2011) (141)
Semi-Supervised QA with Generative Domain-Adaptive Nets (2017) (138)
On Multiplicative Integration with Recurrent Neural Networks (2016) (136)
Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks (2014) (130)
Learning Stochastic Feedforward Neural Networks (2013) (129)
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks (2019) (128)
A Better Way to Pretrain Deep Boltzmann Machines (2012) (128)
Learning Robust Visual-Semantic Embeddings (2017) (127)
Modeling Documents with Deep Boltzmann Machines (2013) (124)
Point Cloud GAN (2018) (121)
Geometry of Optimization and Implicit Regularization in Deep Learning (2017) (116)
Learning in Markov Random Fields using Tempered Transitions (2009) (114)
Discovering Binary Codes for Documents by Learning Deep Generative Models (2011) (113)
Modeling documents with a Deep Boltzmann Machine (2013) (113)
On Unifying Deep Generative Models (2017) (112)
Controllable Text Generation (2017) (109)
Transformer Dissection: An Unified Understanding for Transformer’s Attention via the Lens of Kernel (2019) (105)
Adaptive Overrelaxed Bound Optimization Methods (2003) (104)
Towards Debiasing Sentence Representations (2020) (102)
Self-supervised Learning from a Multi-view Perspective (2020) (102)
Exploiting compositionality to explore a large space of model structures (2012) (100)
Words or Characters? Fine-grained Gating for Reading Comprehension (2016) (99)
MineRL: A Large-Scale Dataset of Minecraft Demonstrations (2019) (97)
Politeness Transfer: A Tag and Generate Approach (2020) (97)
Enhanced Convolutional Neural Tangent Kernels (2019) (97)
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function (2019) (95)
Neural Models for Reasoning over Multiple Mentions Using Coreference (2018) (94)
Hubert: How Much Can a Bad Teacher Benefit ASR Pre-Training? (2021) (92)
Towards Understanding and Mitigating Social Biases in Language Models (2021) (92)
Evaluating probabilities under high-dimensional latent variable models (2008) (90)
Learning Deep Boltzmann Machines using Adaptive MCMC (2010) (88)
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension (2020) (88)
Learning Data Manipulation for Augmentation and Weighting (2019) (87)
Learning Generative Models with Visual Attention (2013) (86)
The Omniglot challenge: a 3-year progress report (2019) (85)
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors (2019) (84)
Deep Lambertian Networks (2012) (83)
On the Convergence of Bound Optimization Algorithms (2002) (82)
A Generic Approach for Escaping Saddle points (2017) (81)
Encode, Review, and Decode: Reviewer Module for Caption Generation (2016) (79)
On Characterizing the Capacity of Neural Networks using Algebraic Topology (2018) (76)
On Reward-Free Reinforcement Learning with Linear Function Approximation (2020) (74)
Video Relationship Reasoning Using Gated Spatio-Temporal Energy Graph (2019) (74)
Resource configurable spoken query detection using Deep Boltzmann Machines (2012) (73)
Active Neural Localization (2018) (73)
Transformation Autoregressive Networks (2018) (72)
Deep Generative Models with Learnable Knowledge Constraints (2018) (72)
Learning and Evaluating Boltzmann Machines (2008) (71)
The Power of Asymmetry in Binary Hashing (2013) (69)
Deep Mixtures of Factor Analysers (2012) (69)
Differentiable Reasoning over a Virtual Knowledge Base (2020) (68)
Knowledge-based Word Sense Disambiguation using Topic Models (2018) (67)
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning (2021) (67)
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations (2014) (67)
Learning Wake-Sleep Recurrent Attention Models (2015) (65)
Gated Path Planning Networks (2018) (64)
Deep Gamblers: Learning to Abstain with Portfolio Theory (2019) (63)
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement (2020) (62)
Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix (2015) (60)
FILM: Following Instructions in Language with Modular Methods (2021) (60)
Tensor Analyzers (2013) (59)
Learning with the weighted trace-norm under arbitrary sampling distributions (2011) (59)
Deep Neural Networks with Massive Learned Knowledge (2016) (58)
Global Pose Estimation with an Attention-Based Recurrent Network (2018) (58)
Capsules with Inverted Dot-Product Attention Routing (2020) (57)
Accurate and conservative estimates of MRF log-likelihood using reverse annealing (2014) (57)
Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization (2019) (50)
How Many Samples are Needed to Estimate a Convolutional Neural Network? (2018) (49)
Annealing between distributions by averaging moments (2013) (47)
Transformer-XL: Language Modeling with Longer-Term Dependency (2018) (47)
Provably Efficient Reinforcement Learning with General Value Function Approximation (2020) (47)
Improving One-Shot Learning through Fusing Side Information (2017) (46)
Learning nonlinear dynamic models (2009) (46)
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning (2021) (45)
Worst Cases Policy Gradients (2019) (44)
Cardinality Restricted Boltzmann Machines (2012) (43)
Exploring Controllable Text Generation Techniques (2020) (42)
Structured Control Nets for Deep Reinforcement Learning (2018) (39)
A Comparative Study of Word Embeddings for Reading Comprehension (2017) (39)
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers (2020) (38)
C-Learning: Learning to Achieve Goals via Recursive Classification (2020) (38)
Linguistic Knowledge as Memory for Recurrent Neural Networks (2017) (36)
Iterative Refinement of the Approximate Posterior for Directed Belief Networks (2015) (36)
Learning to Learn with Compound HD Models (2011) (35)
Topological Sort for Sentence Ordering (2020) (34)
Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis (2020) (32)
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations (2018) (32)
Guest Editors' Introduction: Special Section on Learning Deep Architectures (2013) (32)
Initialization Strategies of Spatio-Temporal Convolutional Neural Networks (2015) (31)
Embodied Multimodal Multitask Learning (2019) (31)
BLOCK-NORMALIZED GRADIENT METHOD: AN EMPIRICAL STUDY FOR TRAINING DEEP NEURAL NETWORK (2018) (27)
Learning To Explore Using Active Neural Mapping (2020) (27)
Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations (2016) (27)
Deep Neural Networks with Multi-Branch Architectures Are Intrinsically Less Non-Convex (2019) (27)
AutoLoss: Learning Discrete Schedules for Alternate Optimization (2018) (27)
SEAL: Self-supervised Embodied Active Learning using Exploration and 3D Consistency (2021) (26)
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification (2021) (26)
Accelerating Robotic Reinforcement Learning via Parameterized Action Primitives (2021) (26)
Normalized Gradient with Adaptive Stepsize Method for Deep Neural Network Training (2017) (25)
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer (2021) (24)
Strong and Simple Baselines for Multimodal Utterance Embeddings (2019) (24)
Contrastive Learning as Goal-Conditioned Reinforcement Learning (2022) (24)
Connecting the Dots Between MLE and RL for Sequence Generation (2018) (23)
“My Way of Telling a Story”: Persona based Grounded Story Generation (2019) (23)
Concept learning as motor program induction: A large-scale empirical study (2012) (23)
External vs. Internal: An Essay on Machine Learning Agents for Autonomous Database Management Systems (2019) (23)
Demystifying Self-Supervised Learning: An Information-Theoretical Framework (2020) (22)
Instabilities of Offline RL with Pre-Trained Neural Representation (2021) (22)
Deep Determinantal Point Process for Large-Scale Multi-label Classification (2017) (22)
Self-supervised Representation Learning with Relative Predictive Coding (2021) (22)
Data-Dependent Path Normalization in Neural Networks (2015) (22)
Complex Transformer: A Framework for Modeling Complex-Valued Sequence (2019) (21)
GLoMo: Unsupervised Learning of Transferable Relational Graphs (2018) (21)
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation (2021) (21)
A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive Learning (2021) (21)
Focused Attention Improves Document-Grounded Generation (2021) (20)
Geometric Capsule Autoencoders for 3D Point Clouds (2019) (20)
Adversarial Robustness Through Local Lipschitzness (2020) (20)
Matrix reconstruction with the local max norm (2012) (20)
Weakly-Supervised Reinforcement Learning for Controllable Behavior (2020) (19)
Neural Methods for Point-wise Dependency Estimation (2020) (19)
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding (2021) (19)
Computational Modeling of Human Multimodal Language : The MOSEI Dataset and Interpretable Dynamic Fusion (2018) (17)
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network (2018) (17)
Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures (2018) (17)
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations (2021) (17)
Question Answering from Unstructured Text by Retrieval and Comprehension (2017) (16)
Case Study: Deontological Ethics in NLP (2020) (16)
Information Obfuscation of Graph Neural Networks (2020) (16)
Learning Not to Learn in the Presence of Noisy Labels (2020) (15)
Robust Predictable Control (2021) (15)
Conditional Contrastive Learning: Removing Undesirable Information in Self-Supervised Representations (2021) (15)
Concurrent Meta Reinforcement Learning (2019) (14)
The Information Geometry of Unsupervised Reinforcement Learning (2021) (14)
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-Alignment (2020) (14)
Deep Neural Networks with Multi-Branch Architectures Are Less Non-Convex (2018) (13)
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs (2021) (13)
Relationship between gradient and EM steps in latent variable models (2003) (13)
Semi-supervised mixture-of-experts classification (2004) (12)
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator (2018) (12)
Learning Neural Networks with Adaptive Regularization (2019) (12)
Grounding Language Models to Images for Multimodal Generation (2023) (12)
Online Sub-Sampling for Reinforcement Learning with General Function Approximation (2021) (12)
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs (2021) (12)
Learning Cognitive Models Using Neural Networks (2018) (11)
On Universal Approximation by Neural Networks with Uniform Guarantees on Approximation of Infinite Dimensional Maps (2019) (10)
Conditional Contrastive Learning with Kernel (2022) (9)
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study (2018) (9)
Unsupervised Domain Adaptation for Visual Navigation (2020) (8)
Investigating the Working of Text Classifiers (2018) (8)
Modular Visual Navigation using Active Neural Mapping (2019) (8)
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations (2022) (8)
On the Complexity of Exploration in Goal-Driven Navigation (2018) (8)
HighMMT: Towards Modality and Task Generalization for High-Modality Representation Learning (2022) (8)
An Efficient Learning Procedure for Deep (2010) (8)
ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers (2021) (8)
Integrating Domain-Knowledge into Deep Learning (2019) (8)
LSTM Iteration Networks: An Exploration of Differentiable Path Finding (2018) (7)
End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents (2021) (7)
Guaranteeing Reproducibility in Deep Learning Competitions (2020) (7)
Bayesian Probabilistic Matrix Factorization: A User Frequency Analysis (2014) (7)
Connecting the Dots Between MLE and RL for Sequence Prediction (2019) (7)
How Many Samples are Needed to Learn a Convolutional Neural Network? (2018) (6)
Style Transfer Through Multilingual and Feedback-Based Back-Translation (2018) (6)
A New Learning Algorithm for Stochastic Feedforward Neural Nets (2013) (6)
Notes on the KL-divergence between a Markov chain and its equilibrium distribution (2008) (6)
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL (2021) (6)
On Proximal Policy Optimization's Heavy-tailed Gradients (2021) (6)
Learning Language and Multimodal Privacy-Preserving Markers of Mood from Mobile Data (2021) (6)
Graph Adversarial Networks: Protecting Information against Adversarial Attacks (2020) (6)
Imitating Past Successes can be Very Suboptimal (2022) (5)
On Emergent Communication in Competitive Multi-Agent Teams (2020) (5)
Mixtape: Breaking the Softmax Bottleneck Efficiently (2019) (5)
Informedia @ TRECVID 2018: Ad-hoc Video Search, Video to Text Description, Activities in Extended video (2018) (4)
Learning to Hallucinate Examples from Extrinsic and Intrinsic Supervision (2021) (4)
Multimodal Speech Summarization Through Semantic Concept Learning (2021) (4)
Learning Weakly-Supervised Contrastive Representations (2022) (4)
MultiViz: An Analysis Benchmark for Visualizing and Understanding Multimodal Models (2022) (4)
Understanding the Tradeoffs in Client-Side Privacy for Speech Recognition (2021) (4)
Integrating Auxiliary Information in Self-supervised Learning (2021) (4)
Selecting the Best in GANs Family: a Post Selection Inference Framework (2018) (4)
Expectation-conjugate gradient: An alternative to EM (2002) (4)
Deep learning (2014) (4)
Interpretable Multimodal Routing for Human Multimodal Language (2020) (4)
Feature Robust Optimal Transport for High-dimensional Data (2020) (4)
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport (2019) (3)
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks (2021) (3)
Iterative Hierarchical Attention for Answering Complex Questions over Long Documents (2021) (3)
MultiViz: Towards Visualizing and Understanding Multimodal Models (2022) (3)
Effective Data Augmentation With Diffusion Models (2023) (3)
Workshop summary: Workshop on learning feature hierarchies (2009) (2)
Few-Shot Learning with Intra-Class Knowledge Transfer (2020) (2)
Non-linear dimensionality reduction using neural networks (2006) (2)
Uncertainty Quantification with Pre-trained Language Models: A Large-Scale Empirical Analysis (2022) (2)
A Simple Approach to the Noisy Label Problem Through the Gambler's Loss (2019) (2)
PACS: A Dataset for Physical Audiovisual CommonSense Reasoning (2022) (2)
LSMI-Sinkhorn: Semi-supervised Mutual Information Estimation with Optimal Transport (2019) (2)
Simultaneous Localization and Surveying with Multiple Agents (2003) (2)
Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks (2021) (2)
Object Goal Navigation with End-to-End Self-Supervision (2022) (2)
Cross-Task Knowledge Transfer for Visually-Grounded Navigation (2018) (2)
Material for Learning Robust Visual-Semantic Embeddings (2017) (2)
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search (2022) (2)
Analogies Explained: Towards Understanding Word Embeddings (2)
Learning From the Experience of Others: Approximate Empirical Bayes in Neural Networks (2018) (2)
Progressive Knowledge Distillation For Generative Modeling (2019) (2)
EFFICIENT OPTIMIZATION ALGORITHMS FOR LEARNING (2003) (2)
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective (2022) (2)
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control (2022) (2)
Learning Deep Generative Models With Discrete Latent Variables (2018) (2)
Fast Inference and Learning for Modeling Documents with a Deep Boltzmann Machine (2013) (2)
Reasoning over Logically Interacted Conditions for Question Answering (2022) (1)
Conditional Contrastive Learning for Improving Fairness in Self-Supervised Learning (2021) (1)
Offline Reinforcement Learning Workshop at Neural Information Processing Systems, 2020 UNCERTAINTY WEIGHTED OFFLINE REINFORCEMENT LEARNING (2020) (1)
Deep learning models for brain imaging: model depth enhances discovery power (2014) (1)
PixelEDL: Unsupervised Skill Discovery and Learning from Pixels (2021) (1)
Domain Adaptation: Overfitting and Small Sample Statistics (2011) (1)
Domain Adaptation: A Small Sample Statistical Approach (2012) (1)
Discovering Order in Unordered Datasets: Generative Markov Networks (2017) (1)
Learning and Evaluaing Deep Bolztmann Machines (2009) (1)
Combining Programmable Potentials and Neural Networks for Materials Problems (2021) (0)
Neural Topological SLAM for Visual Navigation: Supplementary Material (2020) (0)
Approximate Empirical Bayes for Deep Neural Networks (2018) (0)
Overleaf Example (2021) (0)
VIRTUAL KNOWLEDGE BASE (2020) (0)
Don’t Copy the Teacher: Data and Model Challenges in Embodied Dialogue (2022) (0)
S CALABLE AND P RIVACY - ENHANCED G RAPH G ENER ATIVE M ODEL FOR G RAPH N EURAL N ETWORKS (2022) (0)
Proceedings of the 36th International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA (2019) (0)
Zero-shot Transfer Learning on Heterogeneous Graphs via Knowledge Transfer Networks (2022) (0)
HighMMT: Quantifying Modality&Interaction Heterogeneity for High-Modality Representation Learning (2022) (0)
DIFFERENTIABLE PATH FINDING (2018) (0)
Quantifying & Modeling Feature Interactions: An Information Decomposition Framework (2023) (0)
Efficient Optimization Algorithms for Learning Abstract Efficient Optimization Algorithms for Learning (2003) (0)
Close Category Generalization for Out-of-Distribution Classification (2020) (0)
Plan, Eliminate, and Track -- Language Models are Good Teachers for Embodied Agents (2023) (0)
Tackling AlfWorld with Action Attention and Common Sense from Pretrained LMs (2022) (0)
Self-Supervised Object Goal Navigation with In-Situ Finetuning (2022) (0)
Probing Predictions on OOD Images via Nearest Categories (2020) (0)
Undirected Topic Models (2009) (0)
OTTLENECK ” IN A UTO-ENCODING A RCHITECTURES : AN E MPIRICAL S TUDY (2018) (0)
Graph Generative Model for Benchmarking Graph Neural Networks (2022) (0)
Semi-Supervised Pairing via Basis-Sharing Wasserstein Matching Auto-Encoder (2018) (0)
L EARNING F ACTORIZED M ULTIMODAL R EPRESENTATIONS (2021) (0)
Supplementary Material : Deep Kernel Learning (2016) (0)
Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks (2022) (0)
Planning with Submodular Objective Functions (2020) (0)
Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment (2022) (0)
Scalable Privacy-enhanced Benchmark Graph Generative Model for Graph Convolutional Networks (2022) (0)
Paraphrasing Is All You Need for Novel Object Captioning (2022) (0)
UTML TR 2008 – 002 Learning and Evaluating Boltzmann Machines (2008) (0)
DIFFERENTIABLE MULTI-HOP REASONING OVER A VIRTUAL KNOWLEDGE BASE (2020) (0)
UNKNOWN REWARD FUNCTIONS (2019) (0)
MFM Neural Architecture MFM Generative Network ( b ) MFM Inference Network Inference Network Generative Network (2018) (0)
MultiViz: Towards User-Centric Visualizations and Interpretations of Multimodal Models (2023) (0)
Supplementary for Neural Methods for Point-wise Dependency Estimation (2020) (0)
Learning Markov Chain in Unordered Dataset. (2017) (0)
Zero-shot Domain Adaptation of Heterogeneous Graphs via Knowledge Transfer Networks (2022) (0)

This paper list is powered by the following services:

Other Resources About Russ Salakhutdinov

What Schools Are Affiliated With Russ Salakhutdinov?

Russ Salakhutdinov is affiliated with the following schools:

Russ Salakhutdinov's Academic­Influence.com Rankings

Why Is Russ Salakhutdinov Influential?

Russ Salakhutdinov's Published Works

Published Works

Other Resources About Russ Salakhutdinov

What Schools Are Affiliated With Russ Salakhutdinov?

Image Attributions

Russ Salakhutdinov's AcademicInfluence.com Rankings