Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations.
|
ICML |
2024 |
0 |
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks.
|
ICML |
2024 |
0 |
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks.
|
ICLR |
2024 |
0 |
Probabilistically Rewired Message-Passing Neural Networks.
|
ICLR |
2024 |
0 |
Image Inpainting via Tractable Steering of Diffusion Models.
|
ICLR |
2024 |
0 |
L2XGNN: learning to explain graph neural networks.
|
MLJ |
2024 |
0 |
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models.
|
AAAI |
2023 |
0 |
Learning Neural PDE Solvers with Parameter-Guided Channel Attention.
|
ICML |
2023 |
0 |
Learning Disentangled Discrete Representations.
|
ECML/PKDD |
2023 |
0 |
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching.
|
NIPS/NeurIPS |
2023 |
0 |
SIMPLE: A Gradient Estimator for k-Subset Sampling.
|
ICLR |
2023 |
0 |
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions.
|
TPAMI |
2023 |
0 |
MILIE: Modular & Iterative Multilingual Open Information Extraction.
|
ACL |
2022 |
0 |
BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation.
|
ACL |
2022 |
0 |
PDEBench: An Extensive Benchmark for Scientific Machine Learning.
|
NIPS/NeurIPS |
2022 |
0 |
Ordered Subgraph Aggregation Networks.
|
NIPS/NeurIPS |
2022 |
0 |
Efficient Learning of Discrete-Continuous Computation Graphs.
|
NIPS/NeurIPS |
2021 |
0 |
Learning Sparsity of Representations with Discrete Latent Variables.
|
IJCNN |
2021 |
0 |
Interpreting Node Embedding with Text-labeled Graphs.
|
IJCNN |
2021 |
0 |
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions.
|
NIPS/NeurIPS |
2021 |
23 |
Explaining Neural Matrix Factorization with Gradient Rollback.
|
AAAI |
2021 |
0 |
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders.
|
AAAI |
2021 |
0 |
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs.
|
ICLR |
2021 |
0 |
TransRev: Modeling Reviews as Translations from Users to Items.
|
ECIR |
2020 |
0 |
Learning Discrete Structures for Graph Neural Networks.
|
ICML |
2019 |
203 |
State-Regularized Recurrent Neural Networks.
|
ICML |
2019 |
27 |
MMKG: Multi-modal Knowledge Graphs.
|
ESWC |
2019 |
60 |
A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning.
|
IJCAI |
2019 |
0 |
LRMM: Learning to Recommend with Missing Modalities.
|
EMNLP |
2018 |
16 |
Learning Sequence Encoders for Temporal Knowledge Graph Completion.
|
EMNLP |
2018 |
159 |
KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features.
|
UAI |
2018 |
0 |
Learning Graph Representations with Embedding Propagation.
|
NIPS/NeurIPS |
2017 |
138 |
Discriminative Gaifman Models.
|
NIPS/NeurIPS |
2016 |
36 |
Learning Convolutional Neural Networks for Graphs.
|
ICML |
2016 |
1750 |
Learning and Inference in Tractable Probabilistic Knowledge Bases.
|
UAI |
2015 |
9 |
Lifted Probabilistic Inference for Asymmetric Graphical Models.
|
AAAI |
2015 |
0 |
Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inference.
|
AAAI |
2014 |
60 |
Exchangeable Variable Models.
|
ICML |
2014 |
14 |
RockIt: Exploiting Parallelism and Symmetry for MAP Inference in Statistical Relational Models.
|
AAAI |
2013 |
100 |
Symmetry-Aware Marginal Density Estimation.
|
AAAI |
2013 |
20 |
On the conditional independence implication problem: A lattice-theoretic approach.
|
Artificial Intelligence |
2013 |
0 |
Markov Chains on Orbits of Permutation Groups.
|
UAI |
2012 |
61 |
Log-Linear Description Logics.
|
IJCAI |
2011 |
68 |
Statistical Schema Induction.
|
ESWC |
2011 |
216 |
Fine-Grained Sentiment Analysis with Structural Features.
|
IJCNLP |
2011 |
144 |
A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks.
|
UAI |
2010 |
17 |
Leveraging Terminological Structure for Object Reconciliation.
|
ESWC |
2010 |
100 |
A Probabilistic-Logical Framework for Ontology Matching.
|
AAAI |
2010 |
90 |
Logical Inference Algorithms and Matrix Representations for Probabilistic Conditional Independence.
|
UAI |
2009 |
15 |
On the Conditional Independence Implication Problem: A Lattice-Theoretic Approach.
|
UAI |
2008 |
48 |