International Conference on Learning Representations — 2026
April 23-27, 2026
Riocentro Convention and Event CenterRio de Janeiro
Machine Learning AI
Important Dates
| Submission deadline | September 19, 2025 |
| Notification of acceptance | January 22, 2026 |
ICLR - International Conference on Learning Representations
What It Is
ICLR is one of the premier global conferences in machine learning. It emphasizes representation learning, including deep learning, and welcomes both theoretical advances and practical applications.
Who Should Submit
- Researchers advancing neural architectures, optimization, and learning theory
- Authors presenting new methods for unsupervised, supervised, and reinforcement learning
- Practitioners applying representation learning in areas such as vision, language, speech, healthcare, or robotics
- Scholars contributing reproducible studies, benchmarks, or interpretability research
Who Should Attend
- Academics and students seeking exposure to the latest breakthroughs in deep learning and AI
- Industry professionals applying machine learning in real-world products and services
- Policymakers and entrepreneurs interested in the impact of AI on society and technology
Why It Matters
ICLR is a hub for cutting-edge ideas in representation learning, fostering open discussion, reproducibility, and collaboration across academia and industry. It shapes the direction of deep learning research and its transformative applications worldwide.
Venue
Riocentro Convention and Event Center
Av. Salvador Allende, 6555 - Barra da Tijuca, Rio de Janeiro, Brazil
🔗 View full venue details
Algorithmic Fairness Across Alignment Procedures and Agentic Systems
Examines fairness and bias in the context of RLHF, constitutional AI, and agentic systems - how alignment procedures can encode...
Agents in the Wild: Safety and Security
Addresses safety, alignment, and security challenges for AI agents deployed in real-world open-ended environments.
Algorithmic Fairness in AI Systems
Examines fairness, bias, and equity across AI alignment techniques and autonomous agent systems.
AI for Accelerated Materials Design
Covers machine learning methods for materials discovery, property prediction, and inverse design - from graph neural networks on crystal structures...
AI for Materials Design
Applies machine learning to accelerate discovery of new materials for energy, medicine, and advanced manufacturing.
AI for Peace
Explores how AI can support conflict prevention, humanitarian response, and peacebuilding applications.
AI for Partial Differential Equations
Applies machine learning to solving and simulating partial differential equations in physics, climate, and engineering.
Navigating and Addressing Data Problems for Foundation Models
Tackles the data side of foundation model development: curation, deduplication, quality filtering, data contamination detection, and the downstream effects of...
Data Problems for Foundation Models
Tackles data quality, curation, scaling, and contamination challenges in training and evaluating foundation models.
Foundation Models for Science: Real-World Impact and Science-First Design
Brings together researchers applying large foundation models to scientific discovery, with a focus on real-world deployment challenges and domain-specific design...
Foundation Models for Science
Examines how foundation models can be designed and evaluated for scientific discovery across physics, chemistry, and biology.
Integrating Generative and Experimental Platforms for Biomolecular Design
Bridges wet lab biology and generative AI, focusing on how active learning loops between computational models and high-throughput experiments can...
Generative AI in Genomics
Applies generative models to genomic sequence design, protein structure prediction, and biological data synthesis.
Geometry-Grounded Representation Learning
Develops representations and generative models grounded in geometric structure for 3D, spatial, and equivariant learning.
Geometry-grounded Representation Learning and Generative Modeling
Explores how geometric inductive biases - symmetry, equivariance, manifold structure - can improve representation learning and generative models, with applications...
From Human Cognition to AI Reasoning
Draws on cognitive science and psychology to inform AI reasoning research, exploring what human mental models, heuristics, and reasoning failures...
Lifelong Agents: Learning, Aligning, Evolving
Investigates how AI agents can continuously learn new tasks without forgetting old ones, stay aligned with human values over time,...
Lifelong Agents Workshop
Addresses continual learning, alignment, and adaptation in AI agents that operate and improve over extended time horizons.
Learning Meaningful Representations of Life
Focuses on representation learning for biological data - from protein structures to genomics to single-cell data - with the goal...
Meaningful Representations of Life
Applies representation learning to biological data including proteins, genomics, and single-cell sequencing.
Memory for LLM-Based Agentic Systems
Addresses how LLM-based agents can store, retrieve, and reason over information across long horizons - covering episodic memory, working memory...
Memory for LLM-Based Agentic Systems
Studies external memory, retrieval augmentation, and long-context mechanisms for LLM-based agents.
Machine Learning for Remote Sensing
Covers deep learning for satellite imagery, aerial data, and geospatial analysis - including foundation models for Earth observation, change detection,...
Machine Learning for Remote Sensing
Advances ML methods for satellite imagery analysis including land cover mapping, change detection, and weather forecasting.
Machine Learning for Genomics Explorations
Focuses on applying modern deep learning to genomic data: sequence models for DNA and RNA, variant effect prediction, single-cell analysis,...
Machine Learning for Genomics
Advances ML methods for genomic sequence analysis, gene expression, variant calling, and multi-omics integration.
Multimodal Intelligence: Next Token Prediction and Beyond
Explores architectures and training paradigms for multimodal models that go beyond next-token prediction, including diffusion-based generation, discrete tokenization of images...
Multimodal Intelligence Workshop
Examines unified multimodal architectures that go beyond next-token prediction for vision, language, audio, and action.
Real-World Constrained Generative Models
Develops diffusion and flow-based generative models that satisfy real-world constraints and align with human preferences.
AI with Recursive Self-Improvement
Explores the theoretical foundations and practical implications of AI systems that can improve their own learning algorithms, architectures, and training...
Scientific Methods for Understanding Deep Learning
Brings rigorous scientific methodology to understanding the mechanisms, generalization, and emergent behaviors of deep neural networks.
Scaling Post-training for LLMs
Examines how RLHF, DPO, instruction tuning, and other post-training methods scale with compute, data, and model size - and what...
Scaling Post-Training for LLMs
Investigates RLHF, DPO, instruction tuning, and other post-training methods for scaling and aligning large language models.
Time Series in the Age of Large Models
Explores how large pre-trained models can be adapted for time series forecasting, classification, and anomaly detection.
Time Series in the Age of Large Models
Brings together the time series forecasting and large model communities to examine how foundation models can be adapted for sequential...
Test-Time Updates
Investigates methods that allow models to adapt at inference time - including test-time training, in-context learning, chain-of-thought scaling, and retrieval...
Test-Time Updates Workshop
Studies how models can adapt and improve at inference time using test-time training, prompting, and self-correction.
AI Verification in the Wild
Bridges formal verification and machine learning, exploring how to provide provable guarantees about model behavior in safety-critical settings including autonomous...
AI Verification in the Wild
Advances formal verification, testing, and certification of AI systems for safety-critical real-world deployments.
World Models Workshop
Explores internal world models in AI systems for planning, imagination, and model-based reinforcement learning.
Our picks for International Conference on Learning Representations attendees
A curated selection of hotels chosen for location, value, and fit for conference travellers.
Ibis Rio de Janeiro Barra da Tijuca
Avenida Pepe 56, Barra da Tijuca
Budget-friendly hotel along Avenida Pepe offering 240 modern rooms with air conditioning, safes and TVs
LSH Hotel
Av. Lucio Costa 1996, Barra da Tijuca
Luxury beachfront hotel at Pepê Beach featuring a striking modern design, 122 spacious rooms with ocean or mountain views, concierge and room...
Radisson Hotel Barra Rio de Janeiro
Av. Evandro Lins e Silva 600, Barra da Tijuca
Modern hotel near Barra da Tijuca Beach offering rooms with contemporary comforts, rooftop pools for adults and kids, a fitness center, Origens restaurant...
Royalty Barra Hotel
Av. Do Pepe 690, Barra da Tijuca
Modern hotel overlooking Pedra da Gavea with rooms offering sea or mountain views, located near a metro station
Sol da Barra Apart Hotel
Avenida Lucio Costa 880, Barra da Tijuca
Oceanfront boutique hotel facing Barra da Tijuca beach with suites featuring balconies or kitchenettes, offering beach access, an outdoor pool, meeting facilities and...
Windsor Oceanico Hotel
Rua Martinho de Mesquita 129, Barra da Tijuca
Modern hotel steps from Barra da Tijuca beach offering ocean-view rooms and sustainable features, with air conditioning, mini-bars and safes plus a health...
Wyndham Rio Barra
Avenida Lucio Costa 3150, Barra da Tijuca
Oceanfront hotel on Barra da Tijuca Beach with rooms featuring balconies and kitchenettes, multiple outdoor pools, a spa, fitness center and on-site restaurant...
Related reading
-
ICLR 2026 Rio de Janeiro: Travel Guide and Where to Stay
The International Conference on Learning Representations heads to South America for 202...
-
CVPR and SIGCOMM 2026 Denver: Travel Guide and Where to Stay
Two A* conferences. Same venue. Acceptances for both just dropped. CVPR 2026 runs June...
-
CVPR 2026 Denver: Travel Guide and Where to Stay
The IEEE/CVF Conference on Computer Vision and Pattern Recognition returns to Denver fo...