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🎓 I'm a Senior Research Engineer at Noah's Ark Lab at Huawei in Hong Kong.
🔆 My work has mainly been on time series, including anomaly detection, forecasting, root cause analysis/localization, and spatio-temporal graphs. These days I'm getting more involved with robotics.
🌱 As my previous work alludes, my research interests are quite broad. My focus right now is specifically on LLMs and dexterous manipulation.

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Marcus Kalander's Projects

alarm-rca icon alarm-rca

Implementation and datasets for the paper: 'An Influence-based Approach for Root Cause Alarm Discovery in Telecom Network'.

autoformer icon autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

awesome-automl-papers icon awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

awesome-llm-robotics icon awesome-llm-robotics

A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites

darts icon darts

A python library for easy manipulation and forecasting of time series.

dlinear icon dlinear

This is an official implementation for "Are Transformers Effective for Time Series Forecasting?"

pandas icon pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

plotly.py icon plotly.py

The interactive graphing library for Python (includes Plotly Express) :sparkles:

pointllm icon pointllm

[arXiv 2023] PointLLM: Empowering Large Language Models to Understand Point Clouds

riskloc icon riskloc

Implementation of RiskLoc, a method for localizing multi-dimensional root causes.

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