Nicolas Chapados
17 papers · 2003–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (22) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (6) π£ Hot Topic Early Bird
π£
Hot Topic Early Bird
π§
Keyword Pioneer
π
Academic Marathon
(22)
π
Keyword Trendsetter Combo
(3)
π
Keyword Champion
π
Triple Crown
π₯
Mega-Team
(39)
π
Grand Slam
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(55)
β
The Questioner
π
Century Club
(17)
π₯
Unstoppable
(7)
π
Trend Setter
Conferences
ICML (6)
ICLR (5)
NIPS (3)
AAAI (1)
EMNLP (1)
JMLR (1)
Top co-authors
Keywords
time series forecasting
(2)
transformer architecture
(2)
large language model
(2)
benchmark evaluation
(2)
approximate inference
(1)
bayesian inference
(1)
zero-shot learning
(1)
functional data analysis
(1)
attention mechanism
(1)
question answering
(1)
language modeling
(1)
document understanding
(1)
language model evaluation
(1)
covariance estimation
(1)
covariance matrix
(1)
feature selection
(1)
time series
(1)
gaussian process
(1)
gaussian processes
(1)
model selection
(1)
Papers
Context is Key: A Benchmark for Forecasting with Essential Textual Information
ICML 2025
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
ICLR 2025
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
ICLR 2025
UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction
ICML 2025
XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference
EMNLP 2024
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
ICLR 2024
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
ICML 2024
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
NIPS 2024
RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Content
NIPS 2024
Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts
ICML 2023
TACTiS: Transformer-Attentional Copulas for Time Series
ICML 2022
Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting
AAAI 2021
N-BEATS: Neural basis expansion analysis for interpretable time series forecasting
ICLR 2020
Learning to Learn with Conditional Class Dependencies
ICLR 2019
Effective Bayesian Modeling of Groups of Related Count Time Series
ICML 2014
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
NIPS 2007
Extensions to Metric-Based Model Selection
JMLR 2003