MolMix: A Simple Yet Effective Baseline for Multimodal Molecular Representation Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Manolache, Andrei, Tantaru, Dragos, Niepert, Mathias |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
by: Ariguib, Boshra, et al.
Published: (2025)
by: Ariguib, Boshra, et al.
Published: (2025)
Learning (Approximately) Equivariant Networks via Constrained Optimization
by: Manolache, Andrei, et al.
Published: (2025)
by: Manolache, Andrei, et al.
Published: (2025)
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
by: Errica, Federico, et al.
Published: (2023)
by: Errica, Federico, et al.
Published: (2023)
L2XGNN: Learning to Explain Graph Neural Networks
by: Serra, Giuseppe, et al.
Published: (2022)
by: Serra, Giuseppe, et al.
Published: (2022)
How the Optimizer Shapes Learned Solutions in Equivariant Neural Networks
by: Stupariu, Teodor-Mihai, et al.
Published: (2026)
by: Stupariu, Teodor-Mihai, et al.
Published: (2026)
Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
by: Wei, Ziquan, et al.
Published: (2024)
by: Wei, Ziquan, et al.
Published: (2024)
Probabilistic Graph Rewiring via Virtual Nodes
by: Qian, Chendi, et al.
Published: (2024)
by: Qian, Chendi, et al.
Published: (2024)
MolFusion: Multimodal Fusion Learning for Molecular Representations via Multi-granularity Views
by: Cai, Muzhen, et al.
Published: (2024)
by: Cai, Muzhen, et al.
Published: (2024)
Adaptive Physics-informed Neural Networks: A Survey
by: Torres, Edgar, et al.
Published: (2025)
by: Torres, Edgar, et al.
Published: (2025)
Protein Fold Classification at Scale: Benchmarking and Pretraining
by: Chen, Dexiong, et al.
Published: (2026)
by: Chen, Dexiong, et al.
Published: (2026)
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation
by: Chen, Wei, et al.
Published: (2024)
by: Chen, Wei, et al.
Published: (2024)
ChronoGraph: A Real-World Graph-Based Multivariate Time Series Dataset
by: Lutu, Adrian Catalin, et al.
Published: (2025)
by: Lutu, Adrian Catalin, et al.
Published: (2025)
MolReasoner: Toward Effective and Interpretable Reasoning for Molecular LLMs
by: Zhao, Guojiang, et al.
Published: (2025)
by: Zhao, Guojiang, et al.
Published: (2025)
Preference-Based Gradient Estimation for ML-Guided Approximate Combinatorial Optimization
by: Mielke, Arman, et al.
Published: (2025)
by: Mielke, Arman, et al.
Published: (2025)
FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
by: Liu, Sizhe, et al.
Published: (2024)
by: Liu, Sizhe, et al.
Published: (2024)
Simple Yet Effective: An Information-Theoretic Approach to Multi-LLM Uncertainty Quantification
by: Kruse, Maya, et al.
Published: (2025)
by: Kruse, Maya, et al.
Published: (2025)
LOGLO-FNO: Efficient Learning of Local and Global Features in Fourier Neural Operators
by: Kalimuthu, Marimuthu, et al.
Published: (2025)
by: Kalimuthu, Marimuthu, et al.
Published: (2025)
$\texttt{MiniMol}$: A Parameter-Efficient Foundation Model for Molecular Learning
by: Kläser, Kerstin, et al.
Published: (2024)
by: Kläser, Kerstin, et al.
Published: (2024)
SIMPLE: A Gradient Estimator for $k$-Subset Sampling
by: Ahmed, Kareem, et al.
Published: (2022)
by: Ahmed, Kareem, et al.
Published: (2022)
Simple and Effective Specialized Representations for Fair Classifiers
by: Sinigaglia, Alberto, et al.
Published: (2025)
by: Sinigaglia, Alberto, et al.
Published: (2025)
GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning
by: Chu, Xiangxiang, et al.
Published: (2025)
by: Chu, Xiangxiang, et al.
Published: (2025)
Simple Baselines are Competitive with Code Evolution
by: Gideoni, Yonatan, et al.
Published: (2026)
by: Gideoni, Yonatan, et al.
Published: (2026)
SMART: Scalable Mesh-free Aerodynamic Simulations from Raw Geometries using a Transformer-based Surrogate Model
by: Hagnberger, Jan, et al.
Published: (2026)
by: Hagnberger, Jan, et al.
Published: (2026)
A Strong Baseline for Molecular Few-Shot Learning
by: Formont, Philippe, et al.
Published: (2024)
by: Formont, Philippe, et al.
Published: (2024)
Merge then Realign: Simple and Effective Modality-Incremental Continual Learning for Multimodal LLMs
by: Zhang, Dingkun, et al.
Published: (2025)
by: Zhang, Dingkun, et al.
Published: (2025)
Adaptive Width Neural Networks
by: Errica, Federico, et al.
Published: (2025)
by: Errica, Federico, et al.
Published: (2025)
Mol-LLM: Multimodal Generalist Molecular LLM with Improved Graph Utilization
by: Lee, Chanhui, et al.
Published: (2025)
by: Lee, Chanhui, et al.
Published: (2025)
Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks
by: Li, Ang, et al.
Published: (2025)
by: Li, Ang, et al.
Published: (2025)
MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation
by: Naqvi, Syed Rameez, et al.
Published: (2026)
by: Naqvi, Syed Rameez, et al.
Published: (2026)
Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-directed Molecular Generation
by: Park, Jinyeong, et al.
Published: (2024)
by: Park, Jinyeong, et al.
Published: (2024)
Uni-Mol2: Exploring Molecular Pretraining Model at Scale
by: Ji, Xiaohong, et al.
Published: (2024)
by: Ji, Xiaohong, et al.
Published: (2024)
MolWorld: Molecule World Models for Actionable Molecular Optimization
by: Qiao, Yang, et al.
Published: (2026)
by: Qiao, Yang, et al.
Published: (2026)
Dominant Shuffle: A Simple Yet Powerful Data Augmentation for Time-series Prediction
by: Zhao, Kai, et al.
Published: (2024)
by: Zhao, Kai, et al.
Published: (2024)
Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
by: Buckchash, Himanshu, et al.
Published: (2024)
by: Buckchash, Himanshu, et al.
Published: (2024)
GlassMol: Interpretable Molecular Property Prediction with Concept Bottleneck Models
by: Rivera, Oscar, et al.
Published: (2026)
by: Rivera, Oscar, et al.
Published: (2026)
Structure-Aware Fusion with Progressive Injection for Multimodal Molecular Representation Learning
by: Jing, Zihao, et al.
Published: (2025)
by: Jing, Zihao, et al.
Published: (2025)
Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design
by: Zhang, Wengyu, et al.
Published: (2026)
by: Zhang, Wengyu, et al.
Published: (2026)
Masked Omics Modeling for Multimodal Representation Learning across Histopathology and Molecular Profiles
by: Robinet, Lucas, et al.
Published: (2025)
by: Robinet, Lucas, et al.
Published: (2025)
SymDrift: One-Shot Generative Modeling under Symmetries
by: Darouich, Samir, et al.
Published: (2026)
by: Darouich, Samir, et al.
Published: (2026)
A Frustratingly Simple Yet Highly Effective Attack Baseline: Over 90% Success Rate Against the Strong Black-box Models of GPT-4.5/4o/o1
by: Li, Zhaoyi, et al.
Published: (2025)
by: Li, Zhaoyi, et al.
Published: (2025)
Similar Items
-
Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining
by: Ariguib, Boshra, et al.
Published: (2025) -
Learning (Approximately) Equivariant Networks via Constrained Optimization
by: Manolache, Andrei, et al.
Published: (2025) -
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
by: Errica, Federico, et al.
Published: (2023) -
L2XGNN: Learning to Explain Graph Neural Networks
by: Serra, Giuseppe, et al.
Published: (2022) -
How the Optimizer Shapes Learned Solutions in Equivariant Neural Networks
by: Stupariu, Teodor-Mihai, et al.
Published: (2026)